FutureofAmerica’sForestsandRangelandsForestService2020ResourcesPlanningActAssessmentFutureofAmerica’sForestsandRangelandsForestService2020ResourcesPlanningActAssessmentGen.Tech.Rep.WO-102July2023AbstractThe2020ResourcesPlanningAct(RPA)Assessmentsummarizesfindingsaboutthestatus,trends,andprojectedfutureoftheNation’sforestsandrangelandsandtherenewableresourcesthattheyprovide.The2020RPAAssessmentspecificallyfocusesontheeffectsofbothsocioeconomicandclimaticchangeontheU.S.landbase,disturbance,forests,forestproductmarkets,rangelands,water,biodiversity,andoutdoorrecreation.Differingassumptionsaboutpopulationandeconomicgrowth,landusechange,andglobalclimatechangefrom2020to2070largelyinfluencetheoutlookforU.S.renewableresources.Manyofthekeythemesfromthe2010RPAAssessmentcycleremainrelevant,althoughnewdataandtechnologiesallowfordeeperandwiderinvestigation.Landdevelopmentwillcontinuetothreatentheintegrityofforestandrangelandecosystems.Inaddition,thecombinationandinteractionofsocioeconomicchange,climatechange,andtheassociatedshiftsindisturbanceswillstrainnaturalresourcesandleadtoincreasingmanagementandresourceallocationchallenges.Atthesametime,landmanagementandadoptionofconservationmeasurescanreducepressureonnaturalresources.TheRPAAssessmentfindingsandassociateddatacanbeusefultoresourcemanagersandpolicymakersastheydevelopstrategiestosustainnaturalresources.U.S.DepartmentofAgriculture,ForestService.2023.FutureofAmerica’sForestandRangelands:ForestService2020ResourcesPlanningActAssessment.Gen.Tech.Rep.WO-102.Washington,DC.348p.https://doi.org/10.2737/WO-GTR-102.InaccordancewithFederalcivilrightslawandU.S.DepartmentofAgriculture(USDA)civilrightsregulationsandpolicies,theUSDA,itsAgencies,offices,andemployees,andinstitutionsparticipatinginoradministeringUSDAprogramsareprohibitedfromdiscriminatingbasedonrace,color,nationalorigin,religion,sex,genderidentity(includinggenderexpression),sexualorientation,disability,age,maritalstatus,family/parentalstatus,incomederivedfromapublicassistanceprogram,politicalbeliefs,orreprisalorretaliationforpriorcivilrightsactivity,inanyprogramoractivityconductedorfundedbyUSDA(notallbasesapplytoallprograms).Remediesandcomplaintfilingdeadlinesvarybyprogramorincident.Personswithdisabilitieswhorequirealternativemeansofcommunicationforprograminformation(e.g.,Braille,largeprint,audiotape,AmericanSignLanguage,etc.)shouldcontacttheresponsibleAgencyorUSDA’sTARGETCenterat(202)720-2600(voiceandTTY)orcontactUSDAthroughtheFederalRelayServiceat(800)877-8339.Additionally,programinformationmaybemadeavailableinlanguagesotherthanEnglish.Tofileaprogramdiscriminationcomplaint,completetheUSDAProgramDiscriminationComplaintForm,AD-3027,foundonlineathttp://www.ascr.usda.gov/complaint_filing_cust.htmlandatanyUSDAofficeorwritealetteraddressedtoUSDAandprovideintheletteralloftheinformationrequestedintheform.Torequestacopyofthecomplaintform,call(866)632-9992.SubmityourcompletedformorlettertoUSDAby:(1)mail:U.S.DepartmentofAgriculture,OfficeoftheAssistantSecretaryforCivilRights,1400IndependenceAvenue,SW,Washington,DC20250-9410;(2)fax:(202)690-7442;or(3)email:program.intake@usda.gov.USDAisanequalopportunityprovider,employer,andlender.ContentsListofFigures............................................................................................iiListofTables...........................................................................................viiiAcknowledgments.......................................................................................xiExecutiveSummary......................................................................................xvChapter1:KeyFindingsofthe2020RPAAssessment.........................................................1-1Chapter2:Introduction.................................................................................2-1Chapter3:FutureScenarios..............................................................................3-1ClaireB.O’Dea,LindaL.Langner,LindaA.Joyce,JeffreyP.Prestemon,DavidN.WearChapter4:LandResources...............................................................................4-1KurtRiitters,JohnW.Coulston,ChristopherMihiar,EvanB.Brooks,EricJ.Greenfield,MarkD.Nelson,GrantM.Domke,MirandaH.Mockrin,DavidJ.Lewis,DavidJ.NowakChapter5:DisturbancestoForestsandRangelands..........................................................5-1JenniferK.Costanza,FrankH.Koch,MattReeves,KevinM.Potter,KarenSchleeweis,KurtRiitters,SarahM.Anderson,EvanBrooks,JohnCoulston,LindaJoyce,PrakashNepal,BenjaminPoulter,JeffreyP.Prestemon,J.MorganVarner,DavidWalkerChapter6:ForestResources..............................................................................6-1JohnW.Coulston,EvanB.Brooks,BrettJ.Butler,JenniferK.Costanza,DavidM.Walker,GrantM.Domke,JesseCaputo,MarlaMarkowski-Lindsay,EmmaM.Sass,BrianF.Walters,JinggangGuoChapter7:ForestProducts...............................................................................7-1CraigM.T.Johnston,JinggangGuo,JeffreyP.PrestemonChapter8:RangelandResources..........................................................................8-1MattReeves,MichaelKrebs,SarahE.McCord,MattFitzpatrick,RogerClaassen,EmilyKachergis,LorettaJ.Metz,BriceB.HanberryChapter9:WaterResources..............................................................................9-1TravisWarziniack,MazdakArabi,PamelaFroemke,RohiniGhosh,HadiHeidari,ShaundraRasmussen,RyanSwartzentruberChapter10:Biodiversity:WildlifeandAquaticBiota........................................................10-1RebeccaL.Flitcroft,GwendolynnW.Bury,LindaA.Joyce,ShannonL.Kay,MichaelS.Knowles,MarkD.Nelson,TravisWarziniackChapter11:OutdoorRecreationandWilderness............................................................11-1EricM.White,AshleyE.Askew,J.M.BowkerAppendixA:ListofAbbreviationsandAcronyms............................................................A-1AppendixB:ListofChapterCitations.....................................................................B-12020ResourcesPlanningActAssessmentiListofFiguresFigure2-1.RPAAssessmentregionsandsubregions..................2-2Figure4-14.GrosslandusechangeintheconterminousUnitedStatesfrom2000to2012.......................................4-17Figure3-1.Characterizationofthe2020RPAAssessmentscenariosintermsoffuturechangesinatmosphericwarmingandU.S.Figure4-15.Projectednetlandusechangesfrom2020to2070acrosssocioeconomicgrowth.....................................3-3theconterminousUnitedStates,byRPAscenario..............4-17Figure3-2.Relativecomparisonsofchangebymid-centuryFigure4-16.Characterizationofthe2020RPAAssessmentscenariosin(2041to2070)fromthehistoricalperiod(1971to2000)termsoffuturechangesinatmosphericwarmingandUnitedStatesbetweenRPAclimatemodelprojectionsacrossNationalsocioeconomicgrowth....................................4-18ForestSystemregions.....................................3-5Figure4-17.Characteristicsdifferentiatingthe2020RPAAssessmentFigure3-3.ProjectedchangesforNFSRegion6(PacificNorthwest)scenarios..............................................4-18inannualprecipitation(percent)atmid-century(2041to2070)fromthehistoricalperiod(1971to2000)underRCP8.5.........3-6Figure4-18.Projectednetdevelopedlandusechangefrom2020to2070,byRPAregionandRPAscenario...........................4-19Figure3-4.Characteristicsdifferentiatingthe2020RPAAssessmentscenarios................................................3-9Figure4-19.Projectedforestlandnetchangefrom2020to2070,byRPAregionandRPAscenario..................................4-22Figure3-5.PathwayforincorporationofglobalscenariosintoRPAresourceanalyses.....................................3-9Figure4-20.TreecoverchangeforthreeRPAscenariosfrom2020to2070...........................................4-24Figure4-1.NRIareatrendsinlanduseclasses(bars)and5-yearnetchangeinlanduseclasses(lines)intheconterminousFigure4-21.ImperviouscoverchangeforthreeRPAscenariosfromUnitedStatesfrom1982to2012............................4-32020to2070...........................................4-27Figure4-2.NRItrendsin5-yearnetareachangeinlanduseclassesFigure4-22.Projectednetareachangesoffourlandscapedominanceclassesfrom1987to2012byRPAregion...........................4-3acrosstheconterminousUnitedStatesfrom2020to2070.......4-29Figure4-3.AreaofU.S.“forestremainingforest”from2005to2018....4-5Figure4-23.ProjectednetareachangesoffourlandscapeinterfaceclassesacrosstheconterminousUnitedStatesfrom2020to2070.......4-29Figure4-4.Keylandusetransitionsaffectingtheareaof“forestremainingforest”2005to2018..............................4-5Figure4-24.Distributionofprojectedchangesininteriorforestareafrom2020to2070,acrossallRPAscenarios,climateprojections,andFigure4-5.Totalareaandnumberofhousingunitsinthewildland-urbansimulations.............................................4-30interfaceoftheconterminousUnitedStatesin1990and2010.....4-6Figure4-25.Theeffectofclimateprojectiononlandscapedominance,Figure4-6.Percentoftotalareaandpercentoftotalhousingunitsinthedisplayedasmedianprojectedchangefrom2020to2070........4-30wildland-urbaninterfacein2010,byRPAregion...............4-7Figure4-26.Theeffectofclimateprojectiononnaturalinterface,Figure4-7.Percentgrowthinwildland-urbaninterfaceareaanddisplayedasmedianprojectedchangefrom2020to2070........4-31numberofhousingunitsfrom1990to2010,byRPAregion.......4-7Figure4-27.Theeffectofclimateprojectiononinteriorforest,Figure4-8.Per-countynetpercentchangeintotalforestcoverareadisplayedasmedianprojectedchangefrom2020to2070........4-31andinteriorforestcoverarea(38-acreneighborhoodsize)from2001to2016.......................................4-11Figure4-28.TheeffectofRPAscenarioonlandscapedominance,displayedasmedianprojectedchangefrom2020to2070........4-32Figure4-9.TheareaofFIAforestlanduseintheconterminousUnitedStateswithcoreforestcoverstatus(11-acreneighborhoodsize)Figure4-29.TheeffectofRPAscenarioonnaturalinterface,in2001and2016,byRPAregionandownershipcategory.......4-12displayedasmedianprojectedchangefrom2020to2070........4-32Figure4-10.ProportionofFIAforestlandareaacrosstheconterminousFigure4-30.TheeffectofRPAscenariooninteriorforest,UnitedStatesexhibitingalossofcoreforestcoverstatus—displayedasmedianprojectedchangefrom2020to2070........4-322001to2011...........................................4-13Figure4-31.ProjectednetareachangeoffourlandscapedominanceFigure4-11.Meansharesoffivetypesofforestcoveredgewithinaclassesfrom2020to2070,byRPAsubregion.................4-3338-acreneighborhoodofFIAforestlandplotsacrosstheconterminousUnitedStatesin2016,byRPAregionandFigure4-32.Projectednetareachangeoffourlandscapeinterfaceclassesownershipcategory......................................4-14from2020to2070,byRPAsubregion.......................4-33Figure4-12.ShareoftotallandareabydominanceclassandinterfaceFigure4-33.Projectednetchangeofinteriorforestareafrom2020to2070,classin2016,byRPAregion...............................4-15byRPAsubregion.......................................4-34Figure4-13.NetchangeoftotallandareabydominanceclassandFigure5-1.DistributionofforestlandandrangelandinthefourRPAinterfaceclassfrom2001to2016,byRPAregion..............4-15regions.................................................5-2iiFutureofAmerica’sForestsandRangelandsFigure5-2.Percentandareaofforestburnedbylargefires(atleast405haFigure5-23.Areaofforestinvadedandnotinvaded,byownershipwithinintheWesternUnitedStatesand202haintheEasternUnitedStates)FIAforesttypegroups....................................5-28overtimebyburnseveritycategory..........................5-4Figure5-24.TotalnumberanddensityofnonnativeplantspeciesinFigure5-3.ActivefiresdetectedbysatellitesintheSoutheasternUnitedrangelandcounties.......................................5-29States..................................................5-5Figure5-25.AreaofmortalityattributedtobothinsectanddiseaseFigure5-4.Characterizationofthe2020RPAAssessmentscenariosagentsin5-yearintervals,byRPAregion(AlaskaandHawaiiareintermsoffuturechangesinatmosphericwarmingandU.S.includedinthePacificCoastRegion)........................5-30socioeconomicgrowth.....................................5-6Figure5-26.TheproportionofmortalityattributedtononnativeinvasiveFigure5-5.Characteristicsdifferentiatingthe2020RPAAssessmentagentsversusnativeagentsandthosewithunknownoriginin5-yearscenarios...............................................5-7intervals,byRPAregion(AlaskaandHawaiiareincludedinthePacificCoastRegion)....................................5-31Figure5-6.ProjectedannualfiremortalityvolumeovertimeforallRPAscenarios...............................................5-8Figure5-27.ForestmortalitycausedbysouthernpinebeetleinNewYorkandNewJerseyfrom1999to2017.........................5-32Figure5-7.AnnualfiremortalityvolumeforRPAregionsin2020andprojectedin2070forallRPAscenarios.......................5-9Figure5-28.AnnualareasofforestcanopylosseventsattributedtoremovalsandpercentoftotalforestthatwaslosttotheseremovalFigure5-8.AreaofforestforeachforesttypegroupintheFIAevents,1986to2010,byRPAregion........................5-34database,circa2013......................................5-10Figure5-29.Historical(1850to2000)andprojected(2000to2070)averageFigure5-9.AnnualfiremortalityvolumeforwesternforesttypegroupsinannualaciddepositionforeachRPAregion...................5-352020andprojectedin2070forallRPAscenarios..............5-11Figure5-30.MapsofcriticalloadexceedancesforsurfacewaterFigure5-10.Annualfiremortalityvolumeforeasternforesttypegroupsinacidificationforfourperiodsfrom1850to2070...............5-362020,andprojectedin2070forallRPAscenarios..............5-12Figure5-31.SummaryofforestdisturbanceprocessesforlocationswithFigure5-11.Percentandareaofrangelandsburnedbylargefires(atleastforestcoverloss,2001to2010.............................5-37405haintheWesternUnitedStatesand202haintheEasternUnitedStates)overtimebyburnseveritycategory...................5-14Figure5-32.ProportionofFIAforestlandexposedtoremoval,stress,fire,increaseindevelopedland,orincreaseinagricultureobservedwithinaFigure5-12.Averageannualproductionandaverageinterannualvariabilityin4.41-haneighborhoodfrom2001to2010....................5-38U.S.rangelandsfrom1984to2020.........................5-15Figure5-33.ProportionofFIAforestlandineachFIAforesttypegroupinFigure5-13.ProportionofforestlandareaincategoriesofobservedtheEasternUnitedStatesthatwasexposedtoremoval,stress,andfire36-monthSPEIovertime,basedonPRISMclimatedata,1953to2018,events,2001to2010.....................................5-38fortheUnitedStatesandRPAregions.......................5-16Figure5-34.ProportionofFIAforestlandineachFIAforesttypegroupinFigure5-14.Proportionofforestlandareaincategoriesof36-monthSPEItheWesternUnitedStatesthatwasexposedtoremoval,stress,andfireforhistorical(1953to2005)andfuture(2006to2070)periodsusingevents,2001to2010.....................................5-39theRPAclimateprojectionsunderRCP4.5andRCP8.5........5-18Figure6-1.AreaofforestlandbyRPAregionfortheconterminousUnitedFigure5-15.ComparisonofmonthlyproportionofforesttypegroupsStates,1977to2017......................................6-4insevereorextremedroughtforeachoftheRCPsatmid-century(2041to2070)withthesamemetricduringtherecentpastFigure6-2.Netchangestotimberlandarealextentfrom1977to2017for(1991to2020)..........................................5-19foresttypegroupsintheEastandWest.......................6-5Figure5-16.SPEIandtheratioofdead/livetreesbyregioninTexas,Figure6-3.GrowingstockvolumesbyRPAregionfrom1977to2017,2004to2018...........................................5-21byhardwood/softwood....................................6-6Figure5-17.SPEIandrangelandproductionbyregioninTexas,Figure6-4.AverageannualgrowingstockremovalsbyRPAregion1984to2018...........................................5-22from1976to2016,byhardwood/softwood....................6-6Figure5-18.Proportionofrangelandareaincategoriesofobserved6-monthFigure6-5.ForestageclassdistributionfortheEasternandWesternSPEIovertime,basedonPRISMclimatedata,1953to2018.....5-23conterminousUnitedStatesbasedonthemostcurrenttwomeasurementsperforestplotoftheforestinventory.............6-7Figure5-19.Proportionofrangelandareaincategoriesof6-monthSPEIforhistorical(1953to2005)andfuture(2006to2070)periodsFigure6-6.ForestownershipacrosstheconterminousUnitedStatesusingtheRPAclimateprojectionsunderRCP4.5andin2017.................................................6-8RCP8.5...............................................5-24Figure6-7.PrivateandpublictimberlandownershipbyRPAregionandforFigure5-20.EcologicalsubsectionsandtheirassociateddominantvegetationtheconterminousUnitedStates..............................6-8typesforsummarizingSPEIprojections......................5-25Figure6-8.Forestlandgainandlossbyownershipgroupbetween2007Figure5-21.Comparisonofmonthlyproportionofrangelandand2017................................................6-9ecosystemsinsevereorextremedroughtforeachoftheRCPsatmid-century(2041to2070)withthesamemetricduringtheFigure6-9.Percentageoffamilyforestownershipsandfamilyforestrecentpast(1991to2020).................................5-26acreagebysizeofforestholdingsin2013and2018............6-10Figure5-22.PercentofFIAforestplotsinvadedbycounty...........5-27Figure6-10.Percentageoffamilyforestacreageandfamilyforestownershipbyownershipobjectivesin2018...................6-102020ResourcesPlanningActAssessmentiiiFigure6-11.PercentageoffamilyforestacreageandfamilyforestFigure6-33.Forestecosystemtotalcarbonstockchangein2019(historic)ownershipsidentifyingpotentialownershipconcernsin2018....6-11anddecadalprojectionsfor2030to2070byRPAscenario.......6-30Figure6-12.FamilyforestacreageandfamilyforestownershipFigure6-34.Forestremainingforesttotalforestecosystemcarbonstocksdemographicsin2018....................................6-11andstockchangesfor2019andprojectionsto2070foreachRPAscenario-climatefuture,byRPAregion......................6-31Figure6-13.Percentageoflargecorporateforestownershipsbyownershipobjectivesin2018............................6-11Figure6-35.Historicandprojectedtotalharvestedwoodcarbon(Cinharvestedwoodproductsandsolidwastedisposalsites)forstocksFigure6-14.Percentageoflargecorporateforestownershipsidentifyingandstockchangefrom1990to2070,byRPAscenario..........6-32potentialownershipconcernsin2018........................6-12Figure6-36.RelativeimportanceofRPAscenario,climateprojection,andFigure6-15.ImputationapproachesusedintheForestDynamicsbiologyinexplainingthedifferenceinforestecosystemCtrendsfromModel................................................6-132019to2070byRPAregion...............................6-33Figure6-16.Characterizationofthe2020RPAAssessmentscenariosinFigure6-37.HistoricandprojectedcarbonstocksforthemiddleclimatetermsoffuturechangesinatmosphericwarmingandU.S.projectionwithandwithoutanatmosphericenrichmentassumptionforsocioeconomicgrowth....................................6-15theHL,HM,andHHRPAscenarios........................6-34Figure6-17.Characteristicsdifferentiatingthe2020RPAAssessmentFigure7-1.U.S.productionandconsumptionofindustrialroundwood,scenarios..............................................6-15nationwide,1961to2019..................................7-2Figure6-18.Timberlandareachangeperdecade,startingfrom2020andFigure7-2.Historic(1990to2019)andprojected(2020to2030)U.S.lumberprojectedoutto2070,byRPAregionandRPAscenario.........6-17consumption,forsoftwoodandhardwood.....................7-3Figure6-19.Plantedforestareain2020andprojectedto2070fortheFigure7-3.U.S.single-familyandmultifamilyhousingstarts,1959conterminousUnitedStatesbyRPAscenario..................6-17to2020.................................................7-4Figure6-20.Projectednetchangeintimberlandareafrom2020to2070forFigure7-4.Characterizationofthe2020RPAAssessmentscenariosintermstheforesttypegroupswiththelargestarealextentin2020byRPAoffuturechangesinatmosphericwarmingandU.S.socioeconomicscenario-climatefuture...................................6-18growth.................................................7-5Figure6-21.SensitivityoftimberlandareaprojectionstoclimateFigure7-5.Characteristicsdifferentiatingthe2020RPAAssessmentprojectionandRPAscenarioforselectedforesttypegroups......6-19scenarios...............................................7-6Figure6-22.Growingstockvolumeontimberlandin2020andprojectedFigure7-6.ResourcesPlanningActregionsandsubregions............7-8to2070fortheconterminousUnitedStatesbyRPAscenario-climatefuture.................................................6-20Figure7-7.ProjectedaveragepricesforglobalsoftwoodindustrialroundwoodandhardwoodindustrialroundwoodbyRPAscenario,Figure6-23.Historicalandprojectedgrowingstockvolumefor2020to2070,relativeto2015averageprices..................7-9hardwood/softwoodbyRPAscenarioandRPAregion..........6-20Figure7-8.GlobalprimaryenergyproductionfortheIPCCSharedFigure6-24.HistoricalandprojectedannualremovalvolumeontimberlandSocioeconomicPathwaysusedintheRPAAssessment...........7-9acrosstheconterminousUnitedStates,byRPAscenario.........6-21Figure7-9.GlobalsecondaryenergyproductionfortheIPCCSharedFigure6-25.HistoricalandprojectedremovalvolumeontimberlandforSocioeconomicPathwaysusedintheRPAAssessment..........7-10hardwood/softwoodbyRPAscenarioandRPAregion..........6-21Figure7-10.ProjectedaveragepricesforglobalsoftwoodfuelwoodandFigure6-26.Forestagedistributionin2020andprojectedforestagehardwoodfuelwoodbyRPAscenario,2020to2070,relativeto2015distributionin2070byRPAscenariofortheEasternandWesternaverageprices..........................................7-10conterminousUnitedStates................................6-22Figure7-11.Historic(2012to2015)andprojected(2020to2070)globalFigure6-27.Foresttreedistributionbydiameterclassin2020andprojectedwoodpelletconsumptionacrossRPAscenariosandbyregionwithinforesttreedistributionin2070byRPAscenariofortheEasternandtheRPAHMscenario....................................7-11WesternconterminousUnitedStates........................6-23Figure7-12.Historic(1990to2015)andprojected(2020to2070)globalFigure6-28.Forestvolumedistributionbydiameterclassin2020andsoftwoodindustrialroundwoodconsumptionacrossRPAscenariosandprojectedforestvolumedistributionin2070byRPAscenarioforthebyregionwithintheRPAHMscenario......................7-11EasternandWesternconterminousUnitedStates..............6-24Figure7-13.Historic(1990to2015)andprojected(2020to2070)globalFigure6-29.TheshareoftotalforestecosystemcarbonforeachpoolhardwoodindustrialroundwoodconsumptionacrossRPAscenariosin2020................................................6-26andbyregionwithintheRPAHMscenario...................7-12Figure6-30.HistoricandprojectedforestremainingforestabovegroundFigure7-14.Historic(1990to2015)andprojected(2020to2070)globalbiomasscarbonstocksforeachRPAscenario-climatefuture.....6-28newsprintandprintingandwritingpaperconsumptionacrossRPAscenariosandbyregionwithintheRPAHMscenario...........7-13Figure6-31.Alternativefuturecarbonstockandstockchangetrajectories.............................................6-29Figure7-15.Historic(1990to2015)andprojected(2020to2070)U.S.roundwoodproductionbyRPAscenario.....................7-13Figure6-32.HistoricandprojectedforestremainingforesttotalforestecosystemcarbonstocksandstockchangesforeachRPAscenario-Figure7-16.Historic(1990to2015)andprojected(2020to2070)U.S.climatefuture...........................................6-30industrialroundwoodexportsasshareofproductionfortheRPAHMscenario...............................................7-14ivFutureofAmerica’sForestsandRangelandsFigure7-17.Historic(1990to2015)andprojected(2020to2070)U.S.Figure8-2.Areaofnon-FederalrangelandwhererangelandhealthattributesroundwoodproductionbytypefortheRPAHMscenario........7-14exhibitmoderateorlargerdeparturesfromreferenceconditionfrom2011to2015............................................8-5Figure7-18.ProjectedroundwoodproductionbyRPAregionfortheRPAHMscenario,2020to2070................................7-15Figure8-3.Percentofnon-Federalrangelandareawhereinvasivespecieswerepresentbetween2011to2015..........................8-5Figure7-19.ProjectedaveragepricesforU.S.softwoodindustrialroundwoodandhardwoodindustrialroundwoodbyRPAscenario,Figure8-4.Percentofnon-Federalrangelandareawhereannualbromes2020to2070,relativeto2015averageprices.................7-16(Bromusspp.)meetthecriteriaofcoveringamajority(atleast50percent)ofthesoilsurfacefrom2011to2015..................8-6Figure7-20.Historic(1990to2015)andprojectedU.S(2020to2070):lumberproduction,softwoodlumbernetexports,andhardwoodFigure8-5.LevelIIandIIIOmernikecoregionsusedfortheBLMlumbernetexports,byRPAscenario........................7-16rangelandhealthassessment................................8-7Figure7-21.Historic(1990to2015)andprojected(2020to2070)U.S.Figure8-6.PercentofBLMrangelandswherebioticintegrityexhibitsproductionofsoftwoodlumberandhardwoodlumberforthenone-to-slightorslight-to-moderatedeparturefromreferenceRPAHMscenario.......................................7-17conditions(80percentconfidenceinterval)....................8-9Figure7-22.Historic(1990to2015)andprojected(2020to2070)U.S.Figure8-7.PercentofBLMrangelandswheresoilandsitestabilityexhibitswood-basedpanelsproductionandnetexportsbyRPAscenario..7-18none-to-slightorslight-to-moderatedeparturefromreferenceconditions(80percentconfidenceinterval)....................8-9Figure7-23.Historic(1990to2015)andprojected(2020to2070)U.S.wood-basedpanelsproductionbytypefortheRPAHMscenario..7-18Figure8-8.PercentofBLMrangelandswherehydrologicfunctionexhibitsnone-to-slightorslight-to-moderatedeparturefromreferenceFigure7-24.Historic(1990to2015)andprojected(2020to2070)conditions(80percentconfidenceinterval)...................8-10U.S.wood-basedpanelsproductionbyregionfortheRPAHMscenario...............................................7-18Figure8-9.PercentofBLMrangelandswithpresenceofnonnativeinvasiveplantspecies(80percentconfidenceinterval)..........8-11Figure7-25.Historic(1990to2015)andprojected(2020to2070)U.S.pulpproductionbyRPAscenario.......................7-19Figure8-10.AveragebaregroundcoveronBLMrangelands(80percentconfidenceinterval)............................8-12Figure7-26.Historic(1990to2015)andprojected(2020to2070)U.S.pulpproductionbyregionfortheRPAHMscenario........7-19Figure8-11.SpatialdistributionofAllConditionsInventory(ACI)plots,administeredbytheUSDAForestServiceForestInventoryandFigure7-27.Historic(1990to2015)andprojected(2020to2070)AnalysisProgramthroughouttheWesternUnitedStates........8-12U.S.pulpproductionbytypefortheRPAHMscenario.........7-19Figure8-12.Correlationofperennialforbandgrasscover,annualforbFigure7-28.Historic(1990to2015)andprojected(2020to2070)andgrasscover,andbaregroundwithrespecttotimeonrangelands,U.S.paperconsumptionbytypefortheRPAHMscenario.......7-20derivedusingPearson’srfrom1984to2020forecologicalsubsections(BaileyandHogg1986)..................................8-14Figure7-29.Historic(1990to2015)andprojected(2020to2070)U.S.productionofnewsprintandprintingandwritingpaperbyFigure8-13.CorrelationofannualnetprimaryproductivitywithrespectRPAscenario...........................................7-20totimeonrangelandsderivedusingPearson’srfrom1984to2020,1984to1999,and2000to2020............................8-16Figure7-30.Historic(1990to2015)andprojected(2020to2070)U.S.productionofotherpaperandpaperboardbyRPAscenario..7-20Figure8-14.NumberofbeefcattleintheconterminousUnitedStates,nationallyandbyRPAregion..............................8-18Figure7-31.Historic(1990to2015)andprojected(2020to2070)U.S.netexportsofnewsprintandprintingandwritingpaperbyFigure8-15.Numberofsheep,meatgoats,andAngoragoatsintheRPAscenario...........................................7-21conterminousUnitedStates................................8-18Figure7-32.Historic(1990to2015)andprojected(2020to2070)Figure8-16.ProjectedensemblechangeinthestartofthegrowingseasonU.S.netexportsofotherpaperandpaperboardbyRPAscenario..7-21comparedtoa2000to2014baselineforRCP4.5earlycentury,RCP4.5mid-century,RCP8.5earlycentury,andRCP8.5Figure7-33.Historic(1990to2015)andprojected(2020to2070)mid-century............................................8-21U.S.productionofnewsprintandprintingandwritingpaperbyregionfortheRPAHMscenario............................7-21Figure8-17.Projectedensemblechangeintheendofthegrowingseasoncomparedtoa2000to2014baselineforRCP4.5earlycentury,Figure7-34.Historic(1990to2015)andprojected(2020to2070)RCP4.5mid-century,RCP8.5earlycentury,andRCP8.5U.S.productionofotherpaperandpaperboardbyregionforthemid-century............................................8-21RPAHMscenario.......................................7-22Figure8-18.ProjectedensembleproportionalchangeinNPPcomparedFigure7-35.Historic(1990to2015)andprojected(2020to2070)toa2015to2019baselineforRCP4.5earlycentury,RCP4.5U.S.fuelwoodproductionbyRPAscenarioandbyregionforthemid-century,RCP8.5earlycentury,andRCP8.5mid-century...8-22RPAHMscenario.......................................7-22Figure8-19.ProjectedproportionalchangeinNPPfromthe2015to2019Figure7-36.Historic(1990to2015)andprojected(2020to2070)baselinerepresentingthelowestNPPprojections(NPPmin)forRCPU.S.woodpelletproductionbyRPAscenarioandbyregionforthe4.5earlycentury,RCP4.5mid-century,RCP8.5earlycentury,andRPAHMscenario.......................................7-23RCP8.5mid-century.....................................8-24Figure8-1.AreaofCRPundercontractfrom1986to2018fortheRPAregionsandtheconterminousUnitedStates....................8-32020ResourcesPlanningActAssessmentvFigure8-20.ProjectedproportionalchangeinNPPfromthe2015to2019Figure9-17.Spatialchangesin30-yearaverageofannualpotentialbaselinerepresentingthehighestNPPprojections(NPPmax)forRCPevapotranspiration(PET)inresponsetofutureclimatechange,from4.5earlycentury,RCP4.5mid-century,RCP8.5earlycentury,andcurrent(1986–2015)tomid-century(2041–2070)for:RCP4.5andRCP8.5mid-century.....................................8-24RCP8.5...............................................9-15Figure8-21.Projectedchangeinrangelandareacomparedwiththe2012Figure9-18.IntensitiesofwatershortageeventsunderthecurrentbaselineastheensembleofresultsacrossthefiveRPAclimateconditions(1986to2015)inmillioncubicmeterspermonth.....9-16projectionsforRCP4.5earlycentury,RCP4.5mid-century,RCP8.5earlycentury,andRCP8.5mid-century......................8-26Figure9-19.Changesintheintensitiesofwatershortageeventsfromcurrent(1986to2015)tofuture(2041to2070)conditionsunderFigure8-22.VectorsshowthedistanceanddirectionfromeachcitytoRCP4.5...............................................9-17thelocationofthebestcontemporaryclimaticanalogforthatcity’sprojected2080climateunderRCP4.5.......................8-28Figure9-20.Changesintheintensitiesofshortageeventsfromcurrent(1986to2015)tofuture(2041to2070)conditionsunderFigure8-23.VectorsshowthedistanceanddirectionfromeachcitytoRCP8.5...............................................9-17thelocationofthebestcontemporaryclimaticanalogforthatcity’sprojected2080climateunderRCP8.5.......................8-30Figure10-1.Biodiversityofnativeterrestrialspecies(excludingplants)mappedataresolutionof250mi2fortheconterminousUnitedStates,Figure9-1.Characterizationofthe2020RPAAssessmentscenariosintermswithRPAregionalboundariesandtheoutlineoftheMississippiRiveroffuturechangesinatmosphericwarmingandU.S.socioeconomicbasininblue............................................10-2growth.................................................9-3Figure10-2.Estimatedlong-termchangeinthenumberofforest-associatedFigure9-2.Characteristicsdifferentiatingthe2020RPAAssessmentbirdspeciesdetectedfrom1975to2018.....................10-3scenarios...............................................9-4Figure10-3.AquaticbiodiversityoftheconterminousUnitedStatesFigure9-3.Freshwaterwithdrawals(surfaceandgroundwaterandsharemappedataHUC8watershedscale,withtheMississippiRiverofsurface)in2015andaspercentchangefrom2005to2015......9-5basinoutlinedinblue.....................................10-3Figure9-4.Waterwithdrawals(surfaceandgroundwater)foreachsectorFigure10-4.PercentriparianecotoneareaperHUC10watershedinthebyStatein2015..........................................9-5NationalRiparianAreasBaseMapin2020...................10-4Figure9-5.Current(2015)andprojectedfuture(2070)domesticwithdrawalsFigure10-5.Trendintheduckpopulationfrom1955to2019(top);thebyRPAsubregionandRPAscenarioforthefiveRPAclimaterelationbetweencurrent(2019)duckpopulationestimates(CP)fortheprojections..............................................9-610principalduckspecies(speciesgroupedforgreaterandlesserscaup)withreferencetothepopulationobjectives(PO)specifiedinthe2018Figure9-6.Meanpercentchangefromcurrent(2015)toprojectedfutureNorthAmericanWaterfowlManagementPlan,measuredaspercentof(2070)indomesticwaterwithdrawalsacrossallRPAscenario-climateobjective(bottom).......................................10-5futures.................................................9-7Figure10-6.NationaltrendsacrossFWSadministrativewaterfowlflywayFigure9-7.Current(2015)andfuture(2070)industrialwithdrawalsbyRPAboundariesfortotalduckharvestandtotalgooseharvest,from1961tosubregion...............................................9-72019..................................................10-6Figure9-8.Current(2015)andfuture(2070)thermoelectricconsumptiveFigure10-7.NationaltrendsforthewesternandeasternregionsusebyRPAsubregionandRPAscenarioforthefiveRPAclimateforswanpopulationfrom1980to2019andswanharvestfromprojections..............................................9-81962to2019...........................................10-6Figure9-9.Agriculturalfreshwaterwithdrawals.....................9-9Figure10-8.AmericanwoodcockFWSadministrativemanagementregions;populationindexfrom1968to2019;andharvesttrendsFigure9-10.Current(2015)andfuture(2070)agriculturalwithdrawalsbyfrom1999to2018.......................................10-7RPAsubregionbyclimaticpathway(RCP)forthefiveRPAclimateprojections.............................................9-10Figure10-9.MourningdoveFWSadministrativemanagementunits;populationtrendsfrom2003to2019;andharvesttrendsfromFigure9-11.ChangeintotalconsumptiveusebyRPAsubregionandRPA1999to2019...........................................10-8scenarioforthefiveRPAclimateprojections..................9-11Figure10-10.BirdConservationRegionsoftheUnitedStates.........10-8Figure9-12.MeanchangesinconsumptiveusebysectorandRPAsubregionfrom2015to2070,acrossallscenario-climatefutures..........9-12Figure10-11.Long-termincreasesanddecreasesinproportionsofnativebirdpopulationsintheconterminousUnitedStates,Figure9-13.PercentofwateryieldineachStatefromforestsandnational1966to2015...........................................10-9forests,orderedfromwesttoeast...........................9-13Figure10-12.Short-termincreasesanddecreasesinproportionsFigure9-14.Precipitation,wateryield,andpotentialevapotranspirationforofnativebirdpopulationsintheconterminousUnitedStates,thebaselineperiod(1986to2015)..........................9-142005to2015...........................................10-9Figure9-15.Spatialchangesin30-yearaverageofannualprecipitationinFigure10-13.Decreasingorincreasingnativebirdpopulationsintheresponsetofutureclimatechange,fromcurrent(1986-2015)tomid-conterminousUnitedStates,byBirdConservationRegion......10-10century(2041-2070)for:RCP4.5andRCP8.5................9-14Figure10-14.Geographicdistributionsofplant,mollusk,coral,birds,Figure9-16.Spatialchangesin30-yearaverageofannualwateryieldincrustacean,insect,arachnid,mammal,fish,amphibian,andreptileresponsetofutureclimatechange,fromcurrent(1986–2015)tomid-speciesformallylistedundertheEndangeredSpeciesAct......10-11century(2041–2070)for:RCP4.5andRCP8.5...............9-14viFutureofAmerica’sForestsandRangelandsFigure10-15.CumulativenumberofspecieslistedasendangeredorFigure11-2.Characteristicsdifferentiatingthe2020RPAAssessmentthreatenedundertheEndangeredSpeciesAct................10-12scenarios..............................................11-5Figure10-16.Thepercentofvascularplant,vertebrate,andselectFigure11-3.Differencesinnon-Federalforestacrespercapita,invertebratespeciesassociatedwithforesthabitatsdeterminedtobe2012to2040...........................................11-8possiblyextinct,atriskofextinction,secure,orunranked......10-12Figure11-4.Differencesinnon-Federalforestacrespercapita,Figure10-17.HistoricalandcurrentdistributionsofPacifictroutinthe2012to2070...........................................11-8conterminousUnitedStates,withdistributionsofOncorhynchusmykissspp.andotherPacifictrout,andO.clarkiispp................10-13Figure11-5.Changesinweeklynightsreservedpercampgroundbetween2019and2020byweekforUSDAForestServiceregions......11-12Figure10-18.CountofspeciesofgreatestconservationneedlistedinStatewildlifeactionplans,2015...............................10-14Figure11-6.AnnualvisitationtoStateparksystemsbyRPAregionandconterminousUnitedStates,2009to2017...................11-13Figure10-19.Landusestressatwatershedscalesfrom(a)populationgrowthandurbandevelopment;(b)agriculturalexpansion;(c)densityofFigure11-7.Annualvisitationtofederallymanagedoutdoorrecreationmines;(d)densityofpipelines;(e)mining/energy;and(f)aggregateresources.............................................11-13stressacrossallsectors(atHUC10scale).Higherscoresindicategreaterstress...........................................10-18Figure11-8.Spatialcoverageofgeotaggedpostsfrommultiplesocialmediaplatforms(Flickr,Twitter,andInstagram)acrossareasinwesternFigure10-20.TerrestrialClimateStressIndex(TSCI)scoresrankedbyWashingtonandnorthernNewMexico.....................11-14percentile.............................................10-21Figure11-9.ExamplecomparisonofrelativepercapitaparticipationindicesFigure10-21.ThecumulativenumberofprojectionsthatidentifyfutureinexamplescenariosS1andS2............................11-18highstressforeverycell,basedonthesetof20projections.....10-22Figure11-10.Projectedpercapitaparticipationin2070indexedtoFigure10-22.Thenumberofcumulativeprojectionsthatidentifyfuture2012,comparingRPAscenariosLMwithHMandHLwithHHhighstressforNationalForestSystemandU.S.NationalParkServicefordevelopedsitecamping,equestrianridingontrails,motorizedlands,andallotherlands,basedonthesetof20projections.....10-23wateruse,motorizedoff-roaduse,hunting,anddownhillskiingandsnowboarding..........................................11-20Figure10-23.Stresspresentedasanindexfor:futureclimatevulnerability—definedasthenumberofclimatemodelsthatidentifiedanindividualFigure11-11.Projectedpercapitaparticipationin2070indexedto2012cellashighstress;currentaggregatelanduseimpacts;andacomparingRPAscenariosLMwithHMandHLwithHHformountaincombinationofthetwoindicesdevelopedusingthePlustoolinbiking,cross-countryskiingandsnowshoeing,motorizedsnowuse,ArcGISPro2.8.3.......................................10-24floating,swimming,anddayhiking........................11-24Figure10-24.HotspotswithbothhighterrestrialbiodiversityandFigure11-12.Projectedpercapitaparticipationin2070indexedalikelihoodofhighfuturestress...........................10-25to2012comparingRPAscenariosLMwithHMandHLwithHHfordevelopedsiteuse,viewingnature,andfishing,primitiveFigure10-25.Hotspotswithbothhighaquaticbiodiversityandareause,andbirding....................................11-27alikelihoodofhighfuturestress...........................10-25Figure11-1.Characterizationofthe2020RPAAssessmentscenariosintermsoffuturechangesinatmosphericwarmingandU.S.socioeconomicgrowth................................................11-52020ResourcesPlanningActAssessmentviiListofTablesTable3-1.Characteristicsofthefour2020RPAAssessmentTable4-17.Imperviouscoverin2020byRPAregion(percentoftotalarea)scenarios...............................................3-2andprojectedchangesinimperviouscoverin2070fortheaverage,maximum,andminimumscenarios.........................4-26Table3-2.ClimatemodelprojectionsselectedtoreflectdifferentU.S.climatefuturesintheyear2070.........................3-4Table4-18.Imperviouscoverin2020byecoregion(percentoftotalarea)andprojectedchangesinimperviouscoverin2070fortheaverage,Table4-1.Protectedforestcoverandforestlanduseareainthemaximum,andminimumscenarios.........................4-27conterminousUnitedStates,circa2016.......................4-8Table4-19.Projectedchangesinlandscapedominancefrom2020Table4-2.Totalandperiodicnetareachangeinagriculture,developed,to2070acrossallRPAscenarios,climateprojections,andandforestlandcoverfrom2001to2016,byRPAregion........4-10simulations.............................................4-29Table4-3.TotalandperiodicnetchangeininteriorforestcoverareaTable4-20.Projectedmedianchangeinlandscapedominancearea(38-acreneighborhoodsize)from2001to2016,byRPAregion..4-11from2020to2070acrossallRPAscenarios,climateprojections,andsimulations,byRPAregion............................4-29Table4-4.Componentsofinteriorforestcoverarea(38-acreneighborhood)changefrom2001to2016,byRPAregion....................4-12Table4-21.Projectedchangesininterfaceclassareafrom2020to2070acrossallRPAscenarios,climateprojections,andsimulations....4-30Table4-5.Grossandnetchangeofcoreforestcoverstatus(11-acreneighborhood)for2016FIAforestland,byRPAregionandTable5-1.Fiveclimatemodelsselectedtoreflecttherangeofthefullsetofownership..............................................4-1320climatemodelsintheyear2070..........................5-7Table4-6.Componentsofforestcoverareachangefrom2001to2016intheTable5-2.Projectedchangesfrom2020to2070(valueandpercentchange)conterminousUnitedStatesbylandscapedominanceclass.......4-15inoverallannualfiremortalityvolume,firemortalityvolumeasapercentoftotalvolumeinburnedlocations,andannualareasofTable4-7.Componentsofforestcoverareachangefrom2001to2016inthemoderate-andhigh-severityfiresforeachRPAregion..........5-10conterminousUnitedStatesbylandscapeinterfaceclass........4-16Table6-1.FiveclimatemodelprojectionsselectedtoreflecttherangeoftheTable4-8.Fiveclimatemodelsselectedtoreflecttherangeofthefullsetoffullsetof20availableclimatemodelsintheyear2070.........6-1620climatemodelsintheyear2070.........................4-19Table6-2.ProjectednetchangeintimberlandareaandpercentchangeTable4-9.Projectednetlandusechangefrom2020to2070byRPAscenariofrom2020to2070.......................................6-16andclimateprojection....................................4-20Table6-3.Carbonstocks(BMT)andstockchanges(MMTyr-1)fromTable4-10.Projectedgrosslandusechangefrom2020to2070,averaged1990to2020intheconterminousUnitedStatesforforestoverallRPAscenariosandclimateprojections................4-20ecosystempoolsandharvestedwoodpools...................6-25Table4-11.Projectedgrossforestlandchangefrom2020to2070,byRPATable6-4.Projectednetchangeandpercentchangeinforestremainingforestscenarioandclimateprojection.............................4-21areafrom2020to2070fortheconterminousUnitedStates......6-27Table4-12.ComparisonofUSDAForestServicetreecanopycoverandTable6-5.Forestecosystemcarbon,harvestedwoodcarbon,andcarbonphoto-interpretedpercenttreecanopycoverestimatesbyRPAlandusefromlandusetransferstoforestin2019andprojectedto2070,class..................................................4-23byRPAscenario.........................................6-33Table4-13.TopfivecountiesintheconterminousUnitedStatesTable7-1.KeyexogenousdriversofglobaltrendsintheRPAscenarios..7-7withthegreatestprojectedincreasesanddecreasesintreecoverfrom2020to2070fortheaverage,maximum,Table8-1.Non-FederalrangelandareabyRPAregion................8-2andminimumscenarios...................................4-24Table8-2.ApproximateproportionofrangelandundermanagementintheTable4-14.Treecoverin2020byRPAregion(percentoftotalarea)andconterminousUnitedStates.................................8-2projectedchangesintreecoverin2070fortheaverage,maximum,andminimumscenarios......................................4-25Table8-3.Proportionofnon-Federalrangelands(2011to2015)indifferentcategoriesofdeparturefromreferenceconditionsTable4-15.Treecoverin2020byecoregion(percentoftotalarea)andforrangelandhealth.......................................8-4projectedchangesintreecoverin2070fortheaverage,maximum,andminimumscenarios......................................4-25Table8-4.ProportionofStateareawhereselectinvasivespeciesoccur,providedonlyforStateswhereNRIrangelandsamplesTable4-16.TopfivecountiesintheconterminousUnitedStatesintermsarecollected.............................................8-6ofgreatestprojectedincreasesanddecreasesinimperviouscoverfrom2020to2070fortheaverage,maximum,andminimumTable8-5.EstimatedBLMrangelandareawherenonnativeinvasivescenarios..............................................4-26specieswerepresentandabundant(absolutefoliarcover≥25percent)in2018................................................8-11viiiFutureofAmerica’sForestsandRangelandsTable8-6.DistributionofACIplotsandassociated2005to2017Table10-2.Variablesanddatasourcesusedinstressindices.........10-17remeasurementinformation,byUSDAForestServiceregionandState...............................................8-13Table10-3.Fiveclimatemodelsselectedtoreflecttherangeofthefullsetof20climatemodelsintheyear2070....................10-20Table8-7.TotalnumberanddensityofAllConditionsInventory(ACI)plotsinUSDAForestServiceRegions1and4................8-13Table11-1.AcresinStateparksystemsbyRPAregion...............11-3Table8-8.Correlationofperennialforbandgrasscover(PFGC),annualforbTable11-2.AreaofFederallandandpercentage(relativetocombinedandgrasscover(AFGC),andbareground(BG)withrespecttotimeonStates’totalacreage)byRPAregionandFederallandmanagerrangelands,derivedusingPearson’srfrom1984to2020forOmernik’sin2018................................................11-4ecoregions.............................................8-15Table11-3.Acres(1,000s)intheNationalWildernessPreservationTable8-9.RangelandNPPcharacteristicsincludingmean,coefficientofSystembyFederalagencyandRPAregion,circa2012..........11-4variability(ameasureofinterannualvariability),andcorrelation(r)withrespecttotimeforthreeperiods:1984to2020,1984to1999,andTable11-4.Fiveclimatemodelsselectedtoreflecttherangeofthefullsetof2000to2020...........................................8-1620climatemodelsintheyear2070.........................11-6Table8-10.TotalforagebyownershipandlandcoverclassandtheTable11-5.Most-popularoutdoorrecreationactivitiesbyracialandassociatednumberofanimalunitstheselandscansupportonanethnicgroup,2018......................................11-10annualbasisunderdifferentconditionsintheconterminousUnitedStatesfrom1984to2020...........................8-17Table11-6.PercentofU.S.populationage6andolderengaginginoutdoorrecreationactivities,2007,2010,2015,2018..........11-10Table8-11.FiveclimatemodelsselectedtoreflecttherangeofU.S.climatefuturesintheyear2070............................8-19Table11-7.Numberofindividualsage6andolderengaginginoutdoorrecreationactivities(millions),2007,2010,2015,2018........11-11Table8-12.Projectedchangesinstartofseason(SOS)andendofseason(EOS)phenology(Juliandays)forearlycentury(2020toTable11-8.PercentofU.S.populationages6to18engaginginoutdoor2040)andmid-century(2041to2070),comparedwiththebaselinerecreationactivities,2007,2010,2015,2018.................11-11periodof2000to2014...................................8-20Table11-9.NVUM-basedestimatesofrecreationvisits(millions)onNFSTable8-13.ProjectedproportionalchangesinNPPforearlycentury(2020landsacrossfoursitetypesforFY2019andFY2020,withcomputedto2040)andmid-century(2041to2070),comparedwiththebaselinedifferences(millions)betweenthetwotimeperiods...........11-15periodof2015to2019...................................8-23Table11-10.RecreationactivitiesandassumedinitialoutdoorrecreationTable8-14.Projectedpercentchangeinrangelandlanduseforearlycenturyengagementin2012.....................................11-17(2020to2040)andmid-century(2041to2070),comparedwiththe2012baselineunderRCPs4.5and8.5.......................8-25Table11-11.Projectedchangesinpercapitaparticipationbetween2012and2070andtherelationshipofinfluencingfactorstoparticipationTable8-15.ResultsoftheclimateanaloganalysisforRCP8.5.........8-29rate..................................................11-19Table9-1.Principaldrivers,ratesofwithdrawals,andclimatefeedbacksusedTable11-12.Projectednumbersofoutdoorrecreationparticipantsinwateruseprojections....................................9-2(millions)forconterminousUnitedStatesandRPAregionsin2040and2070,averagedacrossfiveclimateprojectionsTable9-2.FiveclimatemodelsselectedtoreflecttherangeofthefullsetofwithineachRPAscenario................................11-3020availableclimatemodelsintheyear2070...................9-3Table11-13.Projectednumbersofdays(millions)ofrecreationTable10-1.NativeaquaticbiodiversityandspeciesendemictoeachengagementforconterminousUnitedStatesandRPAregionsRPAregionforfish,crayfish,andmussels....................10-4in2040and2070,averagedacrossfiveclimateprojectionswithineachRPAscenario................................11-332020ResourcesPlanningActAssessmentixAcknowledgmentsTheResourcesPlanningAct(RPA)AssessmentistheRebeccaL.Flitcroft,USDAForestService,PacificproductofaprogramofresearchcarriedoutbyaNorthwestResearchStationteamofscientistsfromtheForestService,anagencyoftheU.S.DepartmentofAgriculture.LindaHeath,ClaireO’Dea,PamelaFroemke,USDAForestService,RockyLindaLangner(retired),andKevinPottermanagedtheMountainResearchStationresearchandproductionofthisreport.RohiniGhosh,PacificCorp,Portland,OregonTheresearchunderpinningthe2020RPAAssessmentwasconductedbythefollowingscientistsfromvariousUSDAEricJ.Greenfield,USDAForestService,NorthernForestServiceresearchstations,alongwithinternalandResearchStationexternalcooperators(alphabeticallyarranged):JinggangGuo,LouisianaStateUniversitySarahAnderson,USDAForestService,WashingtonOfficeForestManagement,RangeManagement,andBriceB.Hanberry,USDAForestService,RockyVegetationEcologyMountainResearchStationMazdakArabi,ColoradoStateUniversityHadiHeidari,UniversityofMassachusetts-AmherstAshleyE.Askew,UniversityofGeorgiaCraigM.T.Johnston,ConsultingEconomistJ.M.Bowker,USDAForestService,SouthernResearchLindaA.Joyce,USDAForestService,RockyStation(retired)MountainResearchStation(emeritus)EvanB.Brooks,VirginiaTechEmilyKachergis,U.S.DepartmentoftheInterior,U.S.BureauofLandManagementGwendolynnW.Bury,USDAForestService,PacificNorthwestResearchStationthroughOakRidgeInstituteShannonL.Kay,USDAForestService,RockyforScienceandEducationMountainResearchStationBrettJ.Butler,USDAForestService,NorthernMichaelS.Knowles,USDAForestService,RockyResearchStationMountainResearchStationJesseCaputo,USDAForestService,NorthernFrankH.Koch,USDAForestService,SouthernResearchStationResearchStationRogerClaassen,USDANaturalResourcesMichaelKrebs,ConsultingEcologistConservationServiceClaireB.O’Dea,USDAForestService,WashingtonJenniferK.Costanza,USDAForestService,SouthernOfficeResearch&DevelopmentResearchStationLindaL.Langner,USDAForestService,JohnW.Coulston,USDAForestService,SouthernWashingtonOfficeResearch&Development(retired)ResearchStationDavidJ.Lewis,OregonStateUniversityGrantM.Domke,USDAForestService,NorthernResearchStationMarlaMarkowski-Lindsay,UniversityofMassachusettsAmherstMattFitzpatrick,UniversityofMarylandCenterforEnvironmentalScienceSarahE.McCord,USDAAgriculturalResearchServiceLorettaJ.Metz,USDANaturalResourcesConservationServiceChristopherMihiar,USDAForestService,SouthernResearchStation2020ResourcesPlanningActAssessmentxiMirandaH.Mockrin,USDAForestService,NorthernAnumberofotherinternalandexternalcooperatorsResearchStationcontributedtodevelopmentofthisreportindifferentways.Weacknowledgetheseadditionalcontributorstothe2020MarkD.Nelson,USDAForestService,NorthernRPAAssessment(alphabeticallyarranged):ResearchStationSinanAbood,USDAForestService,WashingtonPrakashNepal,USDAForestService,ForestProductsOfficeBiological&PhysicalResourcesLaboratoryDominiqueBachelet,OregonStateUniversityDavidJ.Nowak,USDAForestService,NorthernResearchStation(emeritus)ZanethiaC.Barnett,USDAForestService,SouthernResearchStationJeffreyP.Prestemon,USDAForestService,SouthernResearchStationConsueloM.Brandeis,USDAForestService,SouthernResearchStationKevinM.Potter,USDAForestService,WashingtonOfficeResearch&DevelopmentDonaldEnglish,USDAForestService,RecreationandHeritageResourcesBenjaminPoulter,NASAGoddardSpaceFlightCenter,EarthSciencesDivisionDavidP.Helmers,UniversityofWisconsinShaundraRasmussen,USDAForestService,RockyJohnB.Kim,USDAForestService,PacificNorthwestMountainResearchStationResearchStationMattReeves,USDAForestService,RockyMountainEmmiLia,UniversityofWashingtonResearchStationAnnMaclean,MichiganTechnologicalUniversityKurtRiitters,USDAForestService,SouthernResearchStationPatrickD.Miles,USDAForestService,NorthernResearchStation(retired)EmmaM.Sass,UniversityofMassachusetts-AmherstDeannaH.Olson,USDAForestService,PacificNorthwestResearchStationKarenSchleeweis,USDAForestService,RockyMountainResearchStationBrookePenaluna,USDAForestService,PacificNorthwestResearchStationRyanSwartzentruber,UniversityofTennesseeKarenL.Prentice,U.S.DepartmentoftheInterior,J.MorganVarner,TallTimbersResearchStationU.S.BureauofLandManagementDavidM.Walker,OakRidgeInstituteforScienceandVolkerC.Radeloff,UniversityofWisconsin-EducationMadisonMostafaShartaj,ColoradoStateUniversityBrianF.Walters,USDAForestService,NorthernResearchStationLindaSpencer,USDAForestService,WashingtonOfficeForestManagement,RangeManagement,andTravisWarziniack,USDAForestService,RockyVegetationEcology(retired)MountainResearchStationJordanF.Suter,ColoradoStateUniversityEricM.White,USDAForestService,PacificNorthwestResearchStationGordonToevs,U.S.DepartmentoftheInterior,U.S.BureauofLandManagementDavidN.Wear,USDAForestService,SouthernResearchStation(retired)PeterVogt,EuropeanCommission,JointResearchCentreMichaelWieczorek,U.S.GeologicalSurveySamanthaG.Winder,UniversityofWashingtonSpencerWood,UniversityofWashingtonxiiFutureofAmerica’sForestsandRangelandsTheRPAAssessmentbenefitedfrompeerreviewcommentsSaraOhrel,EnvironmentalProtectionAgencyonthedraftdocument.Thefollowingscientificpeerreviewersgenerouslydonatedtheirtimeandexpertise,ElizabethPerry,MichiganStateUniversityprovidingcommentsthatgreatlyimprovedthefinalreport(alphabeticallyarranged):StephenPrisley,NationalCouncilforAirandStreamImprovementJustinBaker,NorthCarolinaStateUniversityPeterCaldwell,USDAForestServiceGuyRobertson,USDAForestService(retired)DavidCleaves,USDAForestService(retired)SarahCline,USDAForestServiceBrettRoper,USDAForestServiceAdamDaigneault,UniversityofMaineJustinDerner,USDAAgriculturalResearchServiceMichaelSchwartz,USDAForestServiceDonaldEnglish,USDAForestServiceJessicaHalofsky,USDAForestServiceDanielShively,USDAForestServiceKimberlyHall,TheNatureConservancyHealyHamilton,NatureServeJamesSmith,TheNatureConservancyDonaldHodges,UniversityofTennesseeLindaJoyce,USDAForestService(emeritus)TerrySohl,U.S.GeologicalSurveyBradleyKinder,USDAForestServiceShih-ChiehKao,OakRidgeNationalLaboratoryBrentSohngen,OhioStateUniversityLindaLangner,USDAForestService(retired)AllisonLeidner,U.S.NationalAeronauticsandSpaceKennethStrzepek,MassachusettsInstituteofAdministrationTechnologyJeremyLittell,U.S.GeologicalSurveyAudreyMayer,U.S.FishandWildlifeServiceJohnTanaka,UniversityofWyoming(emeritus)AnnaMiller,UtahStateUniversityJohnMitchell,USDAForestService(retired)ChristopherTopik,TheNatureConservancy(retired)JeffreyMorisette,USDAForestServiceDavidWear,USDAForestService(retired)andResourcesfortheFutureThephysicalproductionofthedocumentrequiresagreatdealofwork.AmandaPerryandJoeBrucewereinstrumentalinfacilitatingtheeditingandlayoutofthisdocument.ThecoverwasdesignedbyTeresaJackson.GraphicssupportwasprovidedbyKaileyMarcinkowskiandKathrynRonnenberg.SonjaOswalt,ScottPugh,MatthewTansey,andNathanWalkercreatedandpopulatedanESRIExperienceBuilderwebsitedevotedtoshowcasinginformationandresultsfromthe2020RPAAssessment(accessiblethroughtheRPAAssessmentwebsite).LaraMurray,JamilleSt.Hilaire,andMargaretGregorydevelopedcommunicationsandoutreachmaterials.2020ResourcesPlanningActAssessmentxiiiExecutiveSummaryU.S.DepartmentofAgriculture,ForestService.2023.ExecutiveSummary.In:U.S.DepartmentofAgriculture,ForestService.2023.FutureofAmerica’sForestandRangelands:ForestService2020ResourcesPlanningActAssessment.Gen.Tech.Rep.WO-102.Washington,DC:xv–xviii.https://doi.org/10.2737/WO-GTR-102-ES.The2020ResourcesPlanningAct(RPA)Assessmentisforestsandrangelands.Althoughforestlandareahasbeenthesixthreportpreparedinresponsetothemandatelosttodevelopmentsince1982,gainstoforestsfromotherinthe1974ForestandRangelandRenewableResourceslanduses,primarilyfromconvertedpasture,havemorethanPlanningAct(PublicLaw93–378,88Stat475,asamended).offsettheselosses,resultinginanetincreaseinforestlandThisreportaddresseslandsacrossallownershipsandarea.Theseconversionstoforestlandarealsoprojectedtosummarizesfindingsaboutthestatus,trends,andprojectedslow.Continuedlanduseconversion,drivenprincipallybyfutureofU.S.forests,forestproductmarkets,rangelands,increaseddevelopedlanduse,isultimatelyprojectedtoleadwater,biodiversity,outdoorrecreation,andtheeffectsoftonetlossesofforestlandofbetween1.9and3.7percentsocioeconomicandclimaticchangeupontheseresources.by2070andnetrangelandlossesofbetween1.0and2.3Theresultscaninformresourcemanagersandpolicymakerspercent.Thegreatestincreasesindevelopedlandusebyastheydevelopstrategiestosustainnaturalresources.2070areprojectedfortheRPASouthRegion.ResultinglossImportantdifferencesarefoundregionallyandlocally,offorestlandisprojectedtobehighestintheRPASouthandthoseuniquepatternshighlighttheneedforflexibleRegion,whilerangelandlossishighestinthePacificCoast.adaptationandmanagementstrategies.TheForestService,anagencyoftheU.S.DepartmentofAgriculture,willAsdevelopedlandareahasexpanded,thejuxtapositioncontinuetousetheresultstoinformstrategicplanningandofdevelopedlandwithruralandnaturallandshasalsoforestplanning.increased.The“wildland-urbaninterface”—theareawheredevelopedandnaturallandusesmeetorintermix—increasedThe2020RPAAssessmentoutlookforU.S.resourcesby33percentbetween1990and2010,tocover10percentprovidesprojectedfuturesacrossfourRPAscenariosofalllandand14percentofforestlandin2010.AlthoughthatcontaindifferingassumptionsaboutU.S.andglobalfutureprojectionsofthewildland-urbaninterfacewerepopulationandeconomicgrowth,technologychange,notincludedinthisAssessment,theareaoflandscapesbioenergypreferences,opennessofinternationaltrade,dominatedbydevelopedlandisprojectedtoincreasebywood-energyconsumption,andglobalclimatechangefrom66to114percentbetween2020and2070.Thedistribution2020to2070.anddensityoffuturedevelopmentinrelationtonaturallandscanhaveimplicationsfortheresourcestheyprovide.LanddevelopmentwillcontinuetoIntermsofinteriorforestarea(aproxyforthedegreeofthreatentheintegrityofforestandforestfragmentation),thewesternandSoutheastsubregionsrangelandecosystems.areprojectedtoexperienceadecreaseofinteriorforestarea,whileincreasesareprojectedinthenorthernandDevelopedlanduseintheUnitedStateshascontinuedeasternsubregions,suggestingthatdifferentlocationswilltheexpansionreportedinthe2010RPAandUpdatetoexperiencedifferenteffectstotheremainingforestlands.the2010RPA,butthisexpansionhasslowed.DevelopedlanduseareaisprojectedtocontinueexpandingintheTheincreasingpresenceofdevelopedlandsinareasformerlyfuture—withincreasesrangingbetween42and58percentdominatedbyagriculturalandnaturallanduseshastheby2070acrossthefourRPAscenarios,fromanestimatedpotentialtointroduceawiderangeofthreatstoforestand97.7millionacresin2020.Theseincreasesindevelopedrangelandoverlargeareas.ThehighestratesofforestandlandoccurattheexpenseofallotherlandusesincludingrangelandinvasionbynonnativeplantsacrosstheUnitedStateshaveoccurredneardevelopedlanduses.Risksto2020ResourcesPlanningActAssessmentxvbiodiversityfromlanddevelopmentincludedestructionofpolicymakers.Adaptationoptionssuchasincreasingcriticalhabitats,reductioninconnectivityamonghabitats,reservoirstoragehavelimitedabilitytocurtailshortage,andanddisplacementorisolationofwildlifepopulations.Theseevengroundwatermining—themostpromisingshort-termmultiplepressuresincreasethelong-termvulnerabilityadaptionoption—haslimitedavailabilitytocurtailshortageofwildlifeandbiodiversitytoclimatechange.Landinthelongterm.Inmanyareas,watershortagesarealreadydevelopmentisprojectedtobeadominantthreattowildlifedrivingtransfersofwaterfromagriculturetourbanusers.andbiodiversityacrossmostoftheEasternUnitedStates,Suchtransfersarelikelytobecomemorecommon.andahighrisktowildlifeandbiodiversityintheareasoftheWesternUnitedStatesnearlargeurbanareas.Futuredroughtscanalsoleadtoreductionsinrangelandhealthandproductivity.RecentdroughteventsmaybeLanddevelopmentpressuresonnearbyforestsandresponsibleforreducedrangelandhealthinArizona,NewrangelandsalsoreducetheirabilitytoprovideecosystemMexico,southeastColorado,northwestTexas,westerngoodsandservicessuchasbiodiversity,carbonOklahoma,andsouthwestKansas.InTexas,severedroughtsequestration,woodandfiber,recreationalopportunities,andin2011and2012correspondedwithwidespreadreductionscleanairandwater.Althoughwaterusehasbeendeclininginrangelandproduction,aswellasforestmortality.nationally,itisexpectedtoincreaseinareasexperiencingProlongeddroughtsintheSouthwesternUnitedStatesrapidpopulationgrowthassociatedwithurbanization.TheseandCaliforniaarecreatingconditionsthathavenotbeenincreasesinwateruseareprojectedtooccurlargelyintheexperiencedsinceEuro-Americansettlement.Changesinsouthernandwesternregionsofthecountry,whichareclimatearealsoexpectedtoshortentherangelandgrowingalreadyexperiencingwaterstress.Landdevelopmentisalsoseasonprimarilyduetonutrientlimitations,leadingtoprojectedtoleadtoincreasingstrainsontheabilityofforestsdecreasesinforageavailabilityandassociateddeclinesandrangelandstoprovidenature-basedoutdoorrecreation,inungulatesuccess.Thesenovelconditionswillcreatewithdeclinesinpercapitarecreationavailabilityinlocationschallengesforrangelandmanagerstryingtobalancetheexperiencinglanddevelopment.Inaddition,thelossofsustainableproductionofdomesticungulateswithotherforestlandaltersboththeamountoftotalcarbonstoredinecosystemservices,suchasmaintainingforagereservesfortheNation’sforestsandtherateatwhichforestsaccumulatenativeungulatesandotherspecies.carbon—becauselessforestlandisavailableforsequestration.Theaverageannualareaburnedbylargewildfiresinforestsandrangelandsfrom2000to2017wasmorethandoubleThecombinationandinteractionoftheaveragefrom1984to1999.Thetotalareaofhigh-socioeconomicchange,climatechange,severityfires,aswellasthevolumeoftreeskilledannuallyandtheassociatedshiftsindisturbancesbyfire,isexpectedtoincreasefurtherby2070.Thelargestwillstrainnaturalresourcesandleadtoincreasesinfire-killedtreevolumesareprojectedtohappenincreasingmanagementandresourcedisproportionatelyintheWesternUnitedStatesamongallocationchallenges.Douglas-fir,ponderosapine,andpinyon/juniperforests,aswellaswoodlandhardwoods.ShiftsinthefireregimeSocioeconomicchange,climatechange,andnaturalpatternsposethreatstothoseecosystems,someofwhicharedisturbanceswillalterthefuturehealthandproductivityadaptedtolowerseverityfire.Escalatingfireactivityalsoofnaturalecosystems.Uncertaintyaboutthemagnitudeposesthreatstohumanhealthandproperty,particularlyinofthesechangesdrivesRPAexaminationofalternativethegrowingwildland-urbaninterface.Inaddition,smokeplausiblefutures.PolicymakersandresourcemanagerscanfromwildfireinfluenceswhereandwhenvisitorstakeuseRPAresultstoidentifyareasofpotentialfuturestress,outdoorrecreationtrips.Visitorscouldchoosetoavoidfire-andtostrategicallyinitiateorenhancetargetedmanagementproneareas,reducingeconomicbenefitswhileleadingtoandadaptationactions.increasedrecreation-associatedstrainsandoveruseamongotherforestecosystems.By2070,droughtsareprojectedtooccurmoreoften,lastlonger,andbemoreintense.InthemajorityofexaminedAsdescribedabove,certainforestecosystemsandlocationsclimatefutures,droughtsareprojectedtooccurmostoftenareprojectedtobedisproportionatelyaffectedbychanginginforestandrangelandecosystemsoftheRPARockyconditions.DominantforesttypesintheRockyMountainMountainRegionandthesouthernportionofthePacificRegionincludingDouglas-firandponderosapineareCoastRegion.Someofthefastestgrowingregionsoftheprojectedtolosearea,growingstockvolume,andcarbon.countryareprojectedtobecomethedriest,exposingmoreTheseexpectationsraiseconcernsaboutthesustainabilitypeopletowatershortages.Projectedincreasesinexposureoftheseforests,aswellasthewildlife,recreation,andtodroughtindicatefuturechallengesformanagersandforestproductmanufacturingsectorsthatdependuponthem.RisingsealevelsintheSouthernandEasternUnitedStateshavealreadyledtotransitionsofcoastalforestsxviFutureofAmerica’sForestsandRangelandsintosaltwatermarshes.Althoughnotexplicitlymodeledmostfuturescenarios.However,thepercapitaareaavailableinthisreport,furtherprojectedincreaseswillcontinuethisforforestrecreationisprojectedtoshrinkinmostregionstransitionandincreasedestructionofresidentialhousinginby2070.Whencombinedwithincreasingparticipation,coastalareas,causinggreaterpressureforlanddevelopmentexistingforestrecreationareasintheselocationswillbeawayfromcoasts.Overlargeareas,sucheffectscouldinhighdemand.Developedrecreationsitesandrecreationincreasedemandforwoodproductsforrebuilding,leadinginfrastructureareparticularlylikelytofacehighdemandtoincreasedtimberandproductpricesaswellasincreasedbecauseactivitiesthatrequiredevelopedinfrastructure—timberharvesting.forexample,historicsitevisitation,picnicking,motorizedboating,developedskiing,anddayhiking—areprojectedPressurefromfuturedisturbance(includingwildfire),toseelargegainsinrecreationconsumption.Inaddition,forestconversiontodevelopedland,andforestaging,increasedfrequencyandseverityofdisturbanceassociatedalongwithrisingdemandforforestproducts,isprojectedwithclimatechangemayreducetheavailabilityandtoinfluencecarbonfuturesbothintermsoftheamountconditionofrecreationopportunities,withrecreationistsofcarbonforestsstore(carbonstocks)andannualrateatoptingtorecreateindifferentseasonsorindifferentlocationswhichforestsstorecarbonthroughforestgrowth(carbontoavoiddisturbance.stockchange).Currently,carbonaccumulationthroughgrowthbothinforestsandintheamountofcarbonstoredinLandmanagementandadoptionofharvestedwoodoffsetsmorethan10percentofeconomy-conservationmeasurescanreducewidecarbonemissionsannually.However,forestgrowthpressureonnaturalresources.ratesareprojectedtoslowasforestsage,disturbanceincreases,andforestsareconvertedtootherlanduses.UnderManagementactionscanplaykeyrolesinavoidingorRPAscenarioswheredemandforwoodproductsandthemitigatingtheimpactsofdisturbancesandchangingclimateconversionofforeststootherlandusesarebothhigh,insomeecosystemsatlocalandlandscapescales.Insometheforestecosystemisprojectedtobecomeanetcarbonforests,treatmentssuchasthinningandprescribedfirehavesource.Whiletheincreaseddemandforwoodproductsbeeneffectiveatamelioratingdroughtimpactsandhaveunderthesescenariosisprojectedtoleadtoasubstantialshownthepotentialtoreducetheoccurrenceofhigh-severityannualincreaseincarbonstoredinharvestedwood,thisfires.Activeforestmanagementhasalsobeenusedtowouldonlypartiallyoffsetcarbonemissionsfromtheforestimproveforestgrowthandhealth,includingthedevelopmentecosystem.Thispartialoffsetwouldleadtoareducedsinkofforestplantations,whichfocusestimberproductiononastrengthandthelikelihoodthattheforestsectorwouldsmallerlandbase.Continuedimprovementsinmanagementbecomeanetcarbonsource.techniquesandtheuseofgeneticallyimprovedplantingstockinforestsmanagedfortimbercanincreasetheamountBiodiversityintheconterminousUnitedStatesishighestinoftimberavailableforforestproductsandreduceharvestingtheNorthandSouthRPARegions;however,projectionsforpressureonotherforests.thecomingdecadesindicatethattheseregionsarethemostvulnerabletothestressoflandusechangeintheformoflandTechnologicaladvancesandadoptionoftechnologyandconversiontodevelopment,expansionofagriculturalareas,otherconservationmeasureshaveledtodecreasesinwateranddevelopmentofenergyinfrastructureandmining.Theuse,evenashumanpopulationhasincreased.From2005relativelysmallfederallymanagedlandbaseintheNorthandto2015,surfacefreshwaterwithdrawalsdecreasedin64SouthRegions,whichcanserveasconservationrefugiatopercentofcountiesnationwide.Duringthesameperiod,somebiodiversity,isunlikelytocounteractanywidespreaddomesticwithdrawalsforhouseholdusefellby10percentbiodiversitylossesinthoseregionsinthecomingdecades.nationallydespitean8-percentincreaseinpopulation.AlthoughthePacificCoastandRockyMountainRegionshaveManyofthesegainsinefficiencyhavebeendrivenbyexpansiveareasofFederallands,theirassociatedbiodiversitytechnologicaladvancessuchasrequirementsforlow-flowisprojectedtobeunderhighclimatestress,inpartduetotheirtoiletsandcommunityregulationsthatprohibitnonessentiallocationsathighelevations.Climatechangemaycompromiseturforincentivizetheirremoval.Recentefficiencyincreasestheabilityoffederallymanagedlandstoprovideclimateinirrigationforagricultureandcoolingmethodsforrefugia,andmayforcelandmanagerstoconsidermodifyingthermoelectricpowerplants,especiallyinwater-scarcemanagementapproachestoaccountforwarmertemperatures,regions,haveledtoa7-percentdecreaseinirrigationincreasedintensityofprecipitationevents,andthepotentialwithdrawalsanda34-percentdecreaseinthermoelectricforgreaternumbersofextremeeventssuchasdrought,heat,withdrawalsoverthissametimeperiod.Theseandotherandwildfire.advancesinefficiencyarekeycomponentsofsocialadaptationtowaterscarcityandcouldhelptomitigatesomeAlthoughpercapitaparticipationinoutdoorrecreationimpactsonsocietyunderprojecteddrierconditionsandactivitieswasrelativelystableintheyearsleadinguptoincreasinglyfrequentdrought.2020,populationgrowthhasledtoanincreaseinthenumberofparticipants,andthisgrowthisexpectedtocontinueunder2020ResourcesPlanningActAssessmentxviiPolicychangescanalsoleadtonaturalresourcethisAssessment,agrowingeconomyandshiftsinlanduseimprovements.TheCleanAirActAmendmentsof1990areprojectedtoleadtoincreasedpressuresonU.S.forestshaveresultedinsubstantialsulfurandnitrogenemissionsandrangelands,andgreaterdemandforthegoodsandreductions,withthehighestreductionintheNorthRegion.servicestheyprovide.Projectedclimatechange,inconcertThesereductionshaveenabledsomeecosystemstorecoverwithassociatedchangesininteractingdisturbancessuchasfromyearsofimpactsfromacidrainandeutrophication,wildfireanddrought,directlyaffectsnaturalecosystemsandincreasingresiliencetoclimatechangeandprovidingwillpresentnewchallengesforresourcemanagers.improvedwildlifehabitat.SomeecosystemshaveevenrecoveredtothepointofallowingthereintroductionofThefuturespresentedinthisreportarebasedonapreviouslyextirpatedspecies,includingbrooktroutinthecontinuationofcurrentU.S.naturalresourcemanagementAdirondackMountainsinNewYork.Projectionsdevelopedpoliciesinthefaceofprojectedchangesinclimate,outsideofRPAindicatecontinuedreductionofsulfuranddemographicandeconomicconditions,andsocialnitrogendepositionthrough2070acrosstheUnitedStates.values.OurresultshighlightanumberofareasinwhichpolicymakersandlandmanagersmayexperiencepressureShiftsinurbanizationpatternshaveledtoslowdownsintochangecurrentpoliciesordevelopnewapproaches.certaintrendsthatwereprojectedinthe2010RPA,withThenegativeeffectsontheenvironment,economy,andanassociatedreductioninresourceimpactsoverwhatwassocietyportrayedbymanyofthescenariosinthisRPApreviouslyexpected.TheconversionratetodevelopedlandAssessmentarenotforegoneconclusions.Someoftheuseincreasedfrom1982to1997,thendeclineduntil2012.negativeeffectscanbemodifiedorreducedbytimelyactionsLandcoverdatasuggestthatthisratecontinuedtodeclinefrompolicymakersandlandmanagersandbyadvancedafter2012.Althoughtheareaofdevelopedlandcontinuestomanagementapproachesthatemergefrominvestmentsinincrease,thedecliningrateoftransitionshowsalowerratescienceandtechnology.TheRPAAssessmentalsopointstoofimpactstonaturalareasthanwasprojected.Similarly,severalareasinwhichchangesinchoicesortechnologyhavealthoughforestcoverfragmentationincreasedfrom2001torecentlyreducedpressureonnaturalresources.Additionally,2016inallRPAregionsoverawiderangeofspatialscales,someofthefuturesmaypresentopportunitiesfornewandtherateofforestcoverlossandfragmentationdecreasedimprovedresourceusesandmanagementapproaches.after2006inallregions.TheinteriorforestareaactuallyincreasedintheSouthRegionafter2006.UnderthenewForestsandrangelandsexistwithinbroaderanddynamicprojections,althoughtheoverallforestareaisexpectedtosocietalandecologicalcontexts.Themanylanduses,decreaseacrossallscenarios,theshareofmore-contiguouseconomicsectors,andcompetingandchangingresourceforestisprojectedtoincreaseintheSouthCentral,demandsacrosstheUnitedStatescomplicatehowNortheast,andNorthCentralSubregions.governments,organizations,andlandownersallocatethescarceeconomicresourcestheymanage.TheRPALookingForwardAssessmentseekstoimproveunderstandingofthemultipleandinteractingfactorsthathavecreatedcurrenttrendsTheRPAlegislationrecognizestheimportanceofforestsandandhowweexpectthesefactorsandotherstoaffectrangelandsincontributingtotheAmericanpublic’swell-renewablenaturalresourcesinthefuture.Thisfocusisabeingandqualityoflife.MaintainingforestsandrangelandsuniquecontributionthatprovidesimportantinformationthatareproductiveandprovidearangeofecosystemtopolicymakersandresourcemanagersastheydevelopservicesstartswithcontinualmonitoringandanalysisofthestrategiesforsustainingtheNation’srenewablenaturaleffectsofchangingsocioeconomictrendsandachangingresources.climateontheseresources.AcrossallfuturesevaluatedinxviiiFutureofAmerica’sForestsandRangelandsChapter1KeyFindingsofthe2020RPAAssessmentU.S.DepartmentofAgriculture,ForestService.2023.KeyFindingsofthe2020RPAAssessment.In:U.S.DepartmentofAgriculture,ForestService.2023.FutureofAmerica’sForestandRangelands:ForestService2020ResourcesPlanningActAssessment.Gen.Tech.Rep.WO-102.Washington,DC:1-1–1-11.Chapter1.https://doi.org/10.2737/WO-GTR-102-Chap1The2020ResourcesPlanningAct(RPA)AssessmentsoforRPAscenarioswithhigherlevelsofpopulationandexploresthepresentconditionand50-yearoutlookincomegrowthandlesssounderhotterclimatefutures.ThefortheNation’sforestandrangelandresources.Thischapterincreaseindevelopedlandsisprojectedtooccuratslowerfollowstheorganizationoftheresource-specificchaptersratesthanpreviouslyprojectedinthe2010RPAAssessment.(Chapters4through11).EachsectionprovidesthekeyPriorprojectionswerebasedondatafrom1982to1997,findingsofthecorrespondingchapter,aswellastheresultswhenratesofnewdevelopmentwereincreasing,whilethethatsupportthosefindings.Keyfindingsapplytothe2020RPAlandusechangemodelsuseddatafrom2000toconterminousUnitedStatesunlessotherwisespecified.2012,whenratesweredecreasingfromthepeak(orhighestrate)in1997.ThedeclineintherateofdevelopmentresultsLandResourcesinsmallerprojectedconversionsfromnondevelopedtodevelopedland.Developedlandscontinuetoencroachonnaturalecosystemsandagriculturalareas,withabouthalfofnewdevelopedTheregionaldifferencesinprojectedincreasesofdevelopedlandsconvertingfromforestorrangeland.landareaaregenerallylargerthanwithin-regiondifferencesattributabletoRPAscenarios.ThelargestprojectedincreasesInallRPAregions,thedevelopedlandareagenerallyindevelopedlandareaappearintheRPASouthRegionandexhibitedthelargestnetgainsofalllandusesfrom1982tosmallestinthePacificCoastandRockyMountainRegions.2012.Asaresult,developmentwasaprimarydriverofnetchangesinmostnondevelopedlanduses.AbouthalfofnewForestlandareaincreasedslightlyoverthepastdecades,developedlandsconvertedfromforestorrangeland,whilemostlyattheexpenseofpastureandcroplandareas.Thismostoftheremainderconvertedfromagriculture(cropandtrendisexpectedtoshifttodecreasingforestareaunderallpasture)landuses.Therateoftransitiontodevelopedlandscenarios,althoughatlowerratesthanprojectedbythe2010usefromotherlandusesincreasedfrom1982until1997.Assessment.Althoughtheareaofdevelopedlandcontinuedtoincreaseafter1997,therateoftransitionbegantodecrease.Netgainsfromotherlanduses,principallycropandpastureland,offsetforestlossestodevelopedlandfrom1982toDevelopedlandsareprojectedtocontinuetoexpandinall2012,resultinginaslightnetincreaseinforestlandarea.scenarios,althoughlessthanprojectedinthe2010RPANon-FederalforestlandareaincreasedslightlyintheNorthAssessment.TheexpansionofdevelopedlandsvariesandSouthRegions,stayedstableintheRockyMountainacrossregionsandisprojectedtobelargerunderhighRegion,anddecreasedslightlyinthePacificCoastRegion.socioeconomicgrowthscenariosandsmallerunderhotterPrivatelyownedforestlandareaisprojectedtodeclineinclimatefutures.thefuture,althoughtheprojected50-yearnetlossis35to55percentlowerthanwasprojectedinthe2010Assessment.TheRPAlandusechangemodelsdescribefuturedynamicsWhile91percentofcurrentprivatelyownedforestlandisofprivately-ownedland,wherethechoicesbetweenforest,projectedtoremaininforestusein2070,mostofthelossrangeland,agriculture,anddevelopedlandusesaredrivenisprojectedtoconverttodevelopedland.TheprojectedprincipallybytherelativeeconomicreturnstothosedecreasesinforestlandareaarelargestintheSouthRegionlanduses.Acontinuedincreaseofdevelopedlandareaisandrelativelysmallinallotherregions.projectedunderallRPAscenario-climatefutures,butmore2020ResourcesPlanningActAssessment1-1Forestcoverfragmentationslowedoverthepastdecadeincreaseindeveloped-dominatedanddevelopedinterfacebutcontinuesoverallandisexpectedtocontinueintothearea.Agriculture-dominatedandagricultureinterfaceareafutureforthewesternandsoutheasternsubregions,whiledecreasedinallregionsexcepttheRockyMountainRegion.decreasingslightlyinthenorthandcentralsubregions.ProjectionssuggestacontinuationofthoseregionaltrendsunderallRPAscenario-climatefutures,exceptforareversalForestlandcoverfragmentationincreasedinallRPAregionsofagriculturetrendsintheRockyMountainRegion.Thisfrom2001to2016,althoughatadecreasingrateafter2006.leadstoadecreaseinnatural-dominatedandagriculture-Anetlossof2.6percentofforestcoverfrom2001to2016naturalinterfacelands,alongsideanincreaseindeveloped-resultedinanoverallnetlossof6.4percentofthe“interior”naturalinterfacelands.forestcover,withregionallossesofinteriorforestrangingfrom2.7percentintheSouthRegionto12.3percentintheEconomicandregionalfactorstendtobemoreimportantRockyMountainRegion.TheanalysisindicatedstabilizationdriversoflanduseareachangesthanchangesinclimaticorrecoveryofinteriorforestintheNorthandSouthRegionsconditions.after2006.LanduseprojectionmodelsstemmingfromintegratedProjectionsholdthatinteriorforestareawilldecreaseunderscenariosofsocioeconomicandclimaticchangeindicatemostRPAscenario-climatefutures,exceptforprojectedthatsocioeconomicfactorstendtobemoreimportantdriversincreasesundera“hot”climatefuture.Theprojectedoffuturelanduseareachangethandochangesinclimaticnationaldecreasesarerelativelysmallacrossscenario-conditions.Similarly,thefuturepatternsoflandusechangeclimatefutures,especiallywhencomparedtoregionalaredrivenmorebythesocioeconomiccomponentsofthechanges.FourRPAsubregionsareprojectedtogaininteriorRPAscenariothanbyprojectedclimaticfactors,exceptinarea(Northeast,NorthCentral,SouthCentral,andGreatless-modifiedlandscapeswherebothdrivershadaboutthePlainsSubregions)whilefourothersareprojectedtosamedegreeofimpact.Intheeconomiclandvaluemodelsloseinteriorarea(PacificSouthwest,PacificNorthwest,underlyingthelanduseprojections,thefinancialreturnsIntermountain,andSoutheastSubregions).todevelopedandagriculturallandusesoftenfarexceedthereturntoalternativelanduses.Therefore,whenlandChangesinunfragmentedforestlandcoveraremoredevelopmentreturnsareprojectedtobehigh,asinthedynamicinprivateforestsoftheSouth,whilechangesinthehigh-growthRPAscenario,conversiontodevelopedlandisWestareslowerandconcentratedinpubliclands.acceleratedregardlessoftheclimateimpact.However,thisacceleratedeffectisdampenedastemperaturesriseintheTheoveralldynamics(i.e.,gainandloss)of“core”forestfuture.cover(unfragmentedforestcoverinthevicinityofforestlanduse)from2001to2016weregreatestonprivatelyDisturbancestoForestsownedlandintheSouthRegion,likelyreflectingtheandRangelandsrelativelylargerareasofharvestandsubsequentforestregenerationinthatregion.Incontrast,mostofthenetTheannualareaoffireinforestsandrangelandshaschange(primarilynetloss)ofcoreforestcoveroccurredincreasedsince1984.TheaverageannualareaburnedonpubliclandinthePacificCoastandRockyMountainbetween2000and2017wasmorethandoublethepre-2000Regionsaverage.Mostforestlandsremainin“natural”landscapes,butFireisessentialinmanyforestandrangelandecosystems,anincreasingproportionisexpectedtobein“interface”butchangesinfireregimescanthreatenthoseecosystems.landscapesneardevelopedoragricultureuseinthefuture.Inforests,largefiresburned0.13percentofthetotalforestareaonaverageannuallybetween1984and2000,Foresttendstobethedominantlandcoverwhereitoccurs;increasingto0.37percentannuallybetween2000andhowever,developedoragriculturelandcovernearforest2017(a189-percentincrease).Inrangelands,thetotalareaposesecologicalrisks.Inboth2001and2016,88percentburnedperyearaveraged0.45percentofthetotalareaofforestcoverareawasinlandscapesdominatedbynaturalsince2000,representinganincreaseof119percentoverthelandcovers(forest,grass,shrub,water,wetland,orbarrenpre-2000averageof0.19percentperyear.Increasingfirecoveroccurringinatleast60percentoftheneighborhoodareatrendsoccurredforforestsandrangelandsinallRPAarea),while31percentwasin“interface”landscapesregionsexceptfortheNorthRegion,wherefireisrelativelycontainingatleast10percentofdevelopedoragriculturerare.Theseincreasesinareaburnedhaveposedchallengeslandcover.formanagementandcanimpacttheabilityofforestsandrangelandstoprovidecleanwater,carbonsequestration,andConsideringalllandarea(notjustforestland),theperiodotherecosystemgoodsandservices.2001to2016sawanetdecreaseinnatural-dominatedandnoninterfaceareainallRPAregions,alongsideanet1-2FutureofAmerica’sForestsandRangelandsThetwowesternRPAregionshavegenerallyhadhigherinsparsedatainsomelocations.Asmoredataareadded,exposuretofireanddroughtthantheeasternregions,aswelladditionalregionalandnationalpatternsmayemerge,thusasthegreatestratesoftreemortalitycausedbyinsectsandprovidingbetterinformationtoprioritizemanagementofdiseases.Incontrast,forestsintheRPASouthRegionhaveinvasivespecies.experiencedthehighestratesofharvestremovals.Fire-causedtreemortalityinforestsisexpectedtoincreaseForestandrangelandecosystemsexperienceavarietyofby2070.Thehighestratesoffiremortalityareexpectedifdisturbancesthatdifferacrossregions.Onaverage,largerclimatefollowsthehotordryclimatefuturesunderanyofforestandrangelandareasburnedannuallyintheRPAthehighwarmingRPAscenarios.PacificCoastandRockyMountainRegionsthanintheeasternregionsfrom2000to2017.ThehighestannualTheannualvolumeofforesttreeskilledbyfireisexpectedburnedareaaveragesoccurredintheRockyMountaintoincreaseovertimeacrosstheUnitedStatesandineachRegion,with403,000haofforestsand638,000haofRPAregionunderallRPAscenario-climatefutures.Annualrangelandsburningperyear.InthePacificCoastRegionfiremortalityvolumeisprojectedtoincreasenationallyanaverageof259,000haofforestsand218,000haofbetween55and108percentfrom2020to2070.Inforestsrangelandsburnedperyear.ForestsinthosetworegionsoftheRPARockyMountainandPacificCoastRegions,alsohadthegreatestareasofmoderate-andhigh-severitywherefireactivityishighest,firemortalityvolumeisfires.ForestsandrangelandsinthePacificCoastRegionprojectedtoincreasebetween20and55percent(RockyandrangelandsintheRockyMountainRegionwereMountainRegion)andbetween63and100percent(Pacificexceptionallydryduringthemid-2010s.AmajordroughtCoastRegion).InadditiontoincreasesinfiremortalityalsooccurredinTexasandotherpartsoftheSouthRegionvolume,increasesintheannualareaofmoderate-severityfrom2011to2012,impactingbothforestsandrangelands.firesareexpectedinallRPAregionsby2070underallRPASummariesofforestcanopymortalityfrominsectandscenarios.InthePacificCoastandSouthRegions,theareadiseaseagentsshowgenerallyhigherratesinthetwoofhigh-severityfiresisalsoexpectedtoincrease.InthewesternRPAregionsthanintheeasternregions.WhiletheRockyMountainandNorthRegions,projectionsindicateRPASouthRegiongenerallyhadlowerratesoffire,drought,thatincreaseordecreaseintheareaofhigh-severityfiresandinsectanddiseaseagents,ithadthehighestannualareadependsontheRPAscenario-climatefuture.Thegreatestofforestharvesting,accountingformorethan65percentincreasesinfiremortalityvolumeandinareasofmoderate-ofallremovalsintheUnitedStateseachyearfrom1986andhigh-severityfiresby2070weregenerallyprojectedbyto2010.ConsiderationoftheseregionaldifferencesintheRPAdryorhotclimatemodelprojectionsunderahighdisturbancescanhelpdirectmanagementandpolicyeffortswarmingfuture(RPAscenariosHL,HM,andHH).Theaimedathelpingforestsadapttochangingconditions.smallestincreaseswereprojectedbytheleastwarmclimatemodelprojection,regardlessoftheRPAscenario.Thehighestratesofinvasionbynonnativeplantsoccurnearagriculturalanddevelopedlanduses,primarilyinforestsinDroughtexposureforforestsandrangelandsisexpectedtotheRPASouthRegionandportionsoftheNorthRegion,andincreaseby2070,andforestandrangelandecosystemsintherangelandsinthePacificCoastRegion.Southwestareexpectedtoexperiencethemostsubstantialincreases.Invasionofforestandrangelandecosystemsbynonnativeplantscancauseecologicalandeconomicimpacts.ForestsTheamountofforestlandandrangelandexperiencingintheRPASouthRegionhadthehighestrateofinvasiondroughtisprojectedtoincreaseunderallRPAclimate(58percent),basedondatacollectedfrom2005to2018,futures.Morethan50percentoftheNation’sforestsandfollowedbytheNorthRegion(55percent).Forestsintherangelandsareprojectedtobeexposedtomoderate,severe,twowesternregionswereconsiderablylessinvaded(8orextremedroughtinmostyearsduringmid-century(2041percentintheRockyMountainRegionand5percentinto2070)bythedryandhotclimateprojectionsunderathePacificCoastRegion).Withinthetwoeasternregions,futurewithhighatmosphericwarming.Underthissameforestsincountiesinthesoutheastern,mid-Atlantic,warmingfuture,themiddleclimateprojectionalsoidentifiesandMidwesternStatesweremostlikelytobeinvadedgreaterthan50-percentexposuretodroughtforbothforestsbynonnativeplants.Thosecountiestendtocontainandrangelandsinmanyyearsduringthatperiod.Wetteragriculturalordevelopedlandusesorarelocatednearconditionsandlowerlevelsofatmosphericwarmingresultinmajormetropolitanareas.Invasionratesofrangelandsbylowerpercentagesofforestareaexposedtodrought.ManynonnativeplantswerehighestinthePacificCoastRegion,forestandrangelandecosystemsintheSouthwestcouldpeakingincoastalCaliforniawhereseveralcountiesseelargeincreasesindroughtexposurebymid-century,nearSanFranciscoandLosAngeleshostmorethan300comparedtorecentlevelsofexposure(1989to2018).Thesenonnativeplantspecies.Collectionofconsistentdataonecosystemsincludethepinyon/juniperwoodlandsforestinvasionbynonnativeplantshasonlyrecentlybeguninbothtypegroupandthegrasslandandcreosotebushdesertscrubforestsandrangelandsacrosstheUnitedStates,resultingrangelandvegetationtypes.2020ResourcesPlanningActAssessment1-3ForestResourcesAbovegroundbiomasscarbondensity(carbonperunitarea)isprojectedtoincreaseby17to25percentover2020Importantforesttypesareexpectedtoloseareaduetoforestdensitiesby2070,whileannualcarbonstockchangeisloss,conversiontoplantedpinefollowingharvest,climate,projectedtodecrease,indicatingcarbonsaturationofU.S.andsuccession.Theseforesttypesincludeaspen/birchintheforests.TheforestecosystemisprojectedtobecomeanetRPANorthRegion,oak/gum/cypressintheSouth,PonderosasourceofCO2by2070underfuturesthatincludehighpineintheRockyMountains,andhemlock/Sitkaspruceinroundwooddemandandnetforestloss.thePacificCoastRegion.Forestsprovideasuiteofecosystemservices,includingForestsprovidemanygoodsandservices.Someofthesethestorageandsequestrationofcarbon.Thedensityofgoodsandservicesarespecifictoindividualforesttypes,abovegroundbiomasscarbonisprojectedtobebetweenandknowledgeofhowthosetypesareprojectedtochange66.8Mgha-1and71.7Mgha-1in2070,representinganisthereforeimportant.Mostforestcommunitytypesareincreaseovertheaveragedensityvaluein2020,andanexpectedtoloseareabetween2020and2070duetoaevenlargerincreaseoverthe1990value.Specifically,combinationofconversiontootherlanduses,harvesttheaveragehectareofforestin2070isprojectedtohaveandplantingtoadifferentspecies,climateeffects,and17to25percentmorecarbonstoredinabovegroundsuccessiontootherforestcommunitytypes.Theextentofbiomassthantheaverageforesthectarehadin2020,andmajorforesttypesintheeasternRPAregionsareprojected51to62percentmorethan1990.ThepoolofcarbonintochangemorethantheforesttypesinthewesternRPAabovegroundbiomassisprojectedtocontinuetoincreaseregions.Theprojectedareasofcommerciallyimportantovertheprojectionperiod,althoughatadecreasingrateforesttypessuchasloblolly/shortleafandDouglas-firduetoconversionofforeststootherlanduses,forestvarymoreinresponsetodifferentRPAscenariosthandisturbances,andaging.Theseresultssuggestthatthetodifferentclimateprojections,whileothertypessuchforestecosystemcarbonsinkwillsaturateinthefuture,aslongleaf/slashpineandmaple/beech/bircharemorewithtotalabovegroundcarbonstockslevelingoffby2070.sensitivetotheclimateprojection.ComparedtootherForestsmaybecomeanetCO2sourceby2070dependingforesttypes,aspen/birchforestsareprojectedtolosetheonforestconversionandroundwooddemand.mostareaby2070.Oak/gum/cypressforestsarealsoprojectedtodeclineinarea,withasubstantialportionlostProjectionssuggestthatharvestedwoodcarbonannualtoloblolly/shortleafforests.Loblolly/shortleafforestsstockchangeratesin2070willbegreaterthannetforestareamongthefewforestcommunitytypesprojectedtoecosystemannualstockchangeratesundermoderate-andincreaseinareaby2070.high-growthfuturescenarios.TimberlandgrowingstockvolumeisprojectedtoincreaseIn2019,forestsectorcarbonstockchangewasattributedthrough2050.Post-2050,growingstockvolumetrajectoriestoforestecosystemcarbonpools(73percent),harvesteddependonroundwooddemandandlandusechoices.woodcarbonpools(14percent),andlanduseconversionstoforest(13percent).AnnualstockchangeratesacrosstheFutureforestvolumeisinfluencedbyshiftsinproductivity,forestsectorareexpectedtodecreasefrom2030to2070,landusechoices,managementactionsandobjectives,andalthoughtheamountofcarbonintheforestecosystemisstillmarkets.Timberlandgrowingstockvolumeisprojectedtoprojectedtoincreaseoverthisperiod.Atthesametime,anincreaseuntil2050.After2050,theprojectedtrajectoriesofincreaseinwoodproductsderivedfromU.S.roundwoodisgrowingstockvolumesvaryacrossRPAscenarios.Underprojected,particularlyundermoderateandhigheconomicRPAscenarioswithlowerdemandforroundwoodandlessgrowthscenarios.Thegreaterannualproductionofwoodforestloss,growingstockvolumeisprojectedtocontinueproductsintheUnitedStatesinthosescenariosleadstotoincreasethrough2070.UnderRPAscenarioswithhigherharvestedwoodcarbon(harvestedwoodproductsinuseroundwooddemandandincreasedforestloss,volumeisandharvestedwoodstoredinsolidwastedisposalsites)projectedtodecreasefrom2050to2070butremainlargeraccumulatingatanincreasingannualrate.Asaresult,thanin2020.Whilescenarioswithhigherroundwoodthecarbonstockchangerateinharvestedwoodcarbonisdemandsuggestfutureswithreducedvolume,the39-toexpectedtobecomelargerthantheforestecosystemcarbon46-percentincreasesinharvestingforproductsinthosestockchangerateasearlyas2060underthemoderateandscenariossupportanexpandingforestproductssector.Thehigheconomicgrowthscenarios.Thissuggeststhatasfuturegrowingstockvolumetrajectoriesandtheirsensitivityforestsmatureandareincreasinglyaffectedbylandusetoroundwooddemandandlandusechangedifferregionally,changeanddisturbance,theharvestedwoodcarbonpoolspointingtoregionalvariabilityinbothprojectedforesttrendswillbecomeincreasinglyimportantforoffsettingemissionsandthepressuresdrivingthosetrends.fromothersectorsoftheeconomy.1-4FutureofAmerica’sForestsandRangelandsAlthoughforestareaincreased3.6percentbetween1977ForestProductsand2017,forestareaisprojectedtodecreasebetween2020and2070,withnetlossesprimarilydrivenbyconversiontoThefutureofU.S.marketsisshapedbystronggrowthindevelopeduses.emergingeconomies,stabletoslightlygrowingdomesticdemands,andbypolicyfactorsrelatedtoenergyembeddedTotalforestareaoftheconterminousUnitedStatesininalternativescenarios.U.S.timberproductionand2017was635.3millionacres,anincreaseof3.6percentconsumptionareprojectedtoremainstrong,withvaryingfrom612.4millionacresin1977;however,forestareaislevelsofgrowthacrossRPAscenarios,butwithimportantprojectedtodecreaseacrossallRPAscenariostobetweenchangesintheproductmix.619and627millionacresin2070.ForestareaprojectionsgenerallyvarymoreinresponsetodifferentRPAscenariosProjectionsofroundwoodproductionareexpectedtoexceedthantodifferentclimateprojections.Theamountoffuturepre-recession(2007to2009)levelsby2070.Growthinforestlossdiffersregionally:theSouthandPacificCoastroundwoodproductionisprojectedtoexceedgrowthinRegionsareprojectedtolosethelargestamountsofforestdomesticconsumptionacrossmostscenarios,thedifferencearea.Lossofforestaffectsarangeofecosystemservices.addingtoU.S.netexports.HighereconomicgrowthForexample,between194and517millionmetrictonsdomesticallyandinternationally(RPAscenariosHHandLM)ofcarboninthesoilareexpectedtobetransferredfromfavorsstrongerexportmarketsforproductcategoriesinwhichforeststootherlandusesfrom2020to2070becauseoftheUnitedStatescurrentlyisalreadyanetexporter:softwoodforestconversion.andhardwoodroundwood,hardwoodlumber,nongraphicspaper(i.e.,otherpaperandpaperboard),andwoodpellets.Thereareanestimated9.6millionfamilyforestownershipsUnderthesesamehigheconomicgrowthscenarios,import-acrosstheUnitedStates,andtheycontrolmoreforestlanddependenceonwood-basedpanelsmoderates,whileimport-thananyotherownershipcategory(39percentexcludingdependenceonsoftwoodlumberdeepens.interiorAlaska).Inallscenarios,U.S.newsprintproductionandconsumptionAcrosstheUnitedStates,anestimated9.6millionfamilydeclinestohistoricallylowlevelsby2070,whileprintingforestownerships(i.e.,individuals,families,trusts,andwritingpaperalsodeclines,butataslowerrate.estates,andfamilypartnerships)guideandmanageMeanwhile,projectionsofotherpaperandpaperboardareforests,withownershippatternsvaryingsubstantiallytiedmorecloselytoeconomicgrowthandrisingoverallamongregions.Nationally,excludinginteriorAlaska,demandforpaperforpackaging.ProjectedU.S.woodpelletfamilyforestownershipscontrolmoreforestlandthanproductionvarieswidelybyscenario,dependingonglobalanyotherownershipgroup.MorethanhalfoftheforestpolicyandshiftsinpreferencesasdefinedbytheRPAlandintheSouthandNorthRegions,56percentand52scenarios.percent,respectively,isownedbymillionsoffamilyforestowners.MostfamilyforestownershaverelativelysmallU.S.industrialroundwoodproductionisprojectedtoriseforestholdings(62percentownlessthan10acres),butfasterthanderivedproductmanufacturingdemand,resultingthemajorityofacresareinrelativelylargerforestholdingsintheUnitedStatescapturingagrowingshareofglobal(58percentoffamilyforestacreageisinholdingsofatindustrialroundwoodexportmarkets.least100acres).Focusingonfamilyforestacreageforownershipswith10+acresofforestland,nearlyhalfisClimatechangeisexpectedtoincreasetimbergrowthrates,ownedbypeoplewhohavecommerciallyharvestedtrees,allowingtimberinventories(stocks)torisedespitegrowingyetonlyarelativelysmallportionoffamilyforestlandproductionofindustrialroundwood.Inaddition,technologyisownedbypeoplewhohavewrittenmanagementplanschangeenablesmanufacturerstoproducemoreoutputper(23percent)orrecentlyreceivedmanagementadvice(34unitofwoodinput.Thesetrendsresultinamarketwherepercent).Throughoutreachandeducation,theforestryindustrialroundwoodsupplygrowsfasterthandemandincommunitycanhelpfamilyforestownersmeettheirneedstheUnitedStates,leadingtorisingexportsofwoodproductsnowandinthefuture.todevelopingeconomiessuchasChinaandIndia.IndustrialroundwoodconsumptioninAsianmarketsisprojectedtoexceedthatoftheNorthAmericanmarketinmostscenariosbymid-century.TheU.S.Southisprojectedtoremainthedominanttimberproducingregionintheworld,producingaround10percentoftotalindustrialroundwoodunderallRPAscenarios.TheinventoryofstandingtimberintheSouthhasrapidlyaccumulatedsincetherecession(2007to2009),which2020ResourcesPlanningActAssessment1-5hasledtoarisingabilityoftimberproducerstosupplycaptureabroadrangeinbioenergydemandconsistentwiththemarket,especiallysoftwoodroundwoodintheSouth.thescenarios’assumptionsaboutfuturesocioeconomicTheSouthproducedaround16percentofglobalsoftwoodconditions,andthusshowtherangeinpossiblefuturesforindustrialroundwoodandaround6percentofhardwoodthewoodpelletmarket.Specifically,themarketforwoodindustrialroundwoodin2015.Eventhoughdemandforpelletsisprojectedtonotgrowsignificantlyorevendeclineroundwoodrisessignificantlyinmostscenariosthroughmid-underlowerandmoderate-growthscenarios(RPAscenarioscentury,dueinlargeparttorapideconomicdevelopmentinHLandHM),whilehigh-growthconditionsassociatedwithChinaandIndia,theUnitedStatesmaintainsitsmarketshareRPAscenarioHHandfavorablepolicyconditionsinherentthrough2070.Dependingonfuturepopulationandeconomicinthemoderate-growthscenarioLMresultinwoodpelletgrowth,theaverageglobalpriceofhardwoodindustrialproductionprojectionsthatmorethandoubleby2070toroundwoodisprojectedtoriseby19to219percentandover20millionmetrictons.softwoodby3to127percentbetween2015and2070.IntheUnitedStates,projectionsindicatepriceincreasesof4to51Ifcurrentpoliciesencouragingwooduseinenergypercentforhardwoodand12to82percentforsoftwood.productionaremaintainedinEurope,theUnitedStatesisprojectedtohaveadurableandgrowingwoodpelletexportTheU.S.papersectorhasundergoneatransitionrelatedtomarketthrough2070.AcrossallRPAscenarios,futuredecliningdemandforgraphicspaperandtheshiftinglobalpelletproductiondoesnotexceed4.2percentoftotalwoodmarketstooverseaspaperproductioninthelast20yearsthatproduction.isprojectedtocontinueintotheforeseeablefuture.Althoughpelletsrepresentasmallfraction(lessthan2TheU.S.productionofnewsprinthasdeclinedfromahighpercent)ofallroundwoodconsumed,woodpelletshaveof6.7millionmetrictonsin2000toaround1millionmetricgrownrapidly,destinedtotheEuropeanUnion(EU)intonsin2018.Newsprintproductionandconsumptionaresupportofthatregion’srenewableenergypolicies.Europeprojectedtodeclinetohistoricallylowlevelsby2070,alongistheworld’slargestwoodpelletproducerandconsumer,withtheproductionandconsumptionofprintingandwritingmainlyowingtotheEU’sbindingrenewableenergytargetspaper,albeitataslowerrate.Althoughindustrialcapacitytofor2020and2030,andotherenvironmentallegislation.producethesetwocategoriesofpaperisprojectedtodeclineThegapbetweenthesupplyanddemandwithintheEUisnationallyasmanufacturingfacilitiesclosealongwithcontributingtotheincreasingimportanceofglobalwooddecliningdemand,nosuchdeclinesareanticipatedforotherpellettrade.Prospectsfordomesticproductionandexportusesofpaper.Infact,growthinotherpaperandpaperboardofwoodpelletsdependinlargepartonstrongoverseasisprojectedtocontinuetorisethroughto2070,offsettingmarkets,whicharelargelymaintainedcurrentlybyEUthedeclinesfromnewsprintandprintingandwritingpaper.policies.WoodpelletmanufacturewouldnotrisetomuchConsequently,U.S.totalwoodpulpproductionisprojectedmorethan4.2percentofallroundwoodconsumptiontogrowby8to39percentnationallybetween2015andby2070underRPAscenarioLMandwouldremainless2070,dependingonthescenario.than1percentunderscenarioHL.ConcernsaboutthesustainabilityandcarbonimplicationsofwoodpelletsasanOverseasdemandforhardwoodroundwoodandlumberenergysourcewouldthereforebemostpronouncedunderprovidesabaseofsupportfordomesticU.S.production.theLMandleastundertheHLscenarios,butinbothcaseswouldnotdefinesubstantialchangesinoverallproduction/TheU.S.housingindustryhashistoricallyprovidedstrongcarbonatthesectorlevel.marketsforsoftwoodroundwood,butmovingforward,marketsforhardwoodroundwoodarelesstiedtothegrowthRangelandResourcesinresidentialhousing.ThesizeofthedomesticmarketfortheU.S.manufactureofwoodfurnitureandotherusesisRangelandhealthisrelativelyunchangedsincethe2010projectedtostagnateoverthecomingdecades,implyingRPAAssessment.ThegreatestoverallimpactstorangelandgreaterrelativeimportanceofhardwoodroundwoodandhealthhavebeenobservedinthePacificCoastRegionandlumberexportmarkets.AllscenariosprojectstableexportinthesouthwesternpartoftheUnitedStatesduetoincreasesmarketsforhardwoodindustrialroundwoodandhardwoodininvasiveannualgrassesanddrought.lumber.RelativelyhealthyrangelandconditionswerefoundonProjectedfuturesintheproductionandconsumptionofapproximately75percentofnon-Federalrangelandfromwoodtogenerateenergydependonpolicyassumptionsand2011to2015andbetween79to86percentofrangelandsconsumerpreferencesandvarywidelybyRPAscenario.managedbytheU.S.BureauofLandManagementfrom2011to2018.Despitetheoverallhealthyconditions,Policychoicesandconsumerpreferencesrelatedtotherecentdatasuggestthatanincreasingextentandmagnitudecarbonbenefitsofwoodenergycanhavestrongimplicationsofinvasiveannualgrassesisreducingrangelandhealth.forthefutureoftheindustry.OurRPAscenariosaimto1-6FutureofAmerica’sForestsandRangelandsReductionsinrangelandhealthareespeciallyacuteinNon-Federalrangelandsoccupiedabout163millionhainthePacificCoastRegion,predominantlyfrominvasive2017,representingalossof6millionha(3.6percent)sinceannualgrasses,whiletheSouthwesternUnitedStateshas1982.Mostlossesweredrivenbynetmovementof2.3experiencedreductionsinrangelandhealthfromreducedmillionhatodevelopeduses(urbanandruraltransportationhydrologicfunctionandbioticintegrity,whichseemtobeinfrastructure)followedbyabout1.2millionhatocroplinkedtonoveldroughtconditions.Itiscurrentlyunclearland.Hotspotsofurbangrowthrateshavebeenobservedwhethertheseeffectsaretransitory,buttheimpactsofsince2010inareadominatedbyrangelandssuchasthoseinvasiveannualgrassesareoftenirreversibleandpresentnearBozeman,MT;Boise,ID;andPhoenix,AZ.Thesenumerousmanagementchallenges.hotspotsofgrowthareprojectedtocontinueinthenearfuture.WhilerangelandlossesareexpectedtobeminorRangelandproductionisincreasinginnorthernpartsofnationally—decreasingjust2.7percentby2070—regionaltherangelandextentanddecreasinginthesouth,withandlocalimpactsareexpectedtobesignificant,especiallycorrespondingchangesinbareground.Interannualwhenconsideringissuessuchashabitatconnectivityvariabilityinproductivityisincreasinginmostareasatandwildlifemigrationroutes.ThePacificCoastRegionthesametime,withthelargestchangessince2000havingisprojectedtolosethemostrangelandarea,about6occurredintheSouthwesternUnitedStates.Currentpercentofthecurrentbase,butsomecountieswithinthatproductiontrendsareprojectedtointensifyinthefutureandregionmayloseupto25percentoftheirrangelandstobecomemorevariableonaninterannualbasis.urbanization.Underahighatmosphericwarmingfuture,61countiesareprojectedtoexhibitlossesexceeding3percentProductivitychangeshaveledtominimalchangesinoverallinthePacificCoastRegion.nationalforageavailability,butregionalandlocalimpactshavebeensignificant.AnnualproductionhasbeenincreasingWaterResourcesacrossthenorthernextentsofconterminousUnitedStatesrangelands,especiallythenorthernGreatPlainsandeasternBothpercapitawateruseandtotalwaterusearedeclininginWashingtonandOregon.Increasesintheannualproductionmanypartsofthecountry.acrossthenorthernGreatPlainshavebeenprimarilyduetoincreasedgrowingseasonprecipitationsince1984andtheWateruseisdrivenbychangesinsocioeconomicandclimatesubsequentincreaseinrangelandwoodiness,whileincreasesvariables,withtherelativeinfluenceofdriversvaryingbyineasternWashingtonandOregonwereprobablyduetosector.Householdwateruseisdrivenlargelybypopulation,theincreasedcoverandextentofinvasiveannualgrasses,butalsobypoliciesandtechnologiesaimedatwaterespeciallycheatgrass(Bromustectorum).Incontrast,conservation.Increaseduseofhigh-efficiencyappliances,rangelandproductivityhasbeendecreasingacrossthelow-flowtoilets,andprogramstolimitoutdoorturfhaveledsouthernextentofrangelands,mostnotablyinthedeserttoremarkabledeclinesinwateruseinmanycommunities,SouthwestandsouthernCalifornia.Decreasesinthoseareaseveninplaceswithpopulationgrowth—domesticwateraredrivenbytheacutedroughtconditionsthathavebeenusedecreasedby10percentfrom2005to2015despitepervasiveforyearstodecades.Inadditiontoasymmetrican8-percentincreaseinpopulation.Percapitahouseholdchangesintheamountofproductionacrossrangelands,withdrawalsfellfrom98gallonsperdayin2005to82interannualvariationinproductionisalsoincreasing,gallonsperdayin2015.Duringthesameperiod,surfaceespeciallysince2000.Thehighestinterannualvariabilityinfreshwaterwithdrawalsdecreasedin64percentofcountiesproductivityoccursintheSouthandPacificCoastRegions.intheconterminousUnitedStatestoabout322billiongallonsperday.Irrigationwithdrawalsfellby7percent,Projectionssuggestthatmanyofthetrendsthathavebeenandthermoelectricwithdrawalsfellby34percent.Someofobservedsince1984—includingdecreasedproductioninthosereductionsinwaterusewerenecessaryduetoextremetheSouth,increasedproductionintheNorth,andgreaterdroughtsthroughoutthelasttwodecades.interannualvariability—willcontinueandpossiblyintensifyinthefuture.TheSouthwestisprojectedtoexperiencethelargestDespitereductionsinwateruse,manyregionsincreasinglyandmostwidespreadreductionsinrangelandproductivity,experiencewatershortagesduetoextendeddryperiods.especiallyindesertareas,followedbythesouthernplainsandFourCornersarea.ThenorthernGreatPlains,especiallyFromhouseholdstoagriculturetoindustry,meaningfulNorthDakota,SouthDakota,andMontana,areprojectedtochangesinhumanbehaviorandconservationpracticeshaveexperiencethelargestgainsinproductivity.resultedinreductionsofwateruse.Nevertheless,largeregionsoftheUnitedStatesfaceincreasingwaterscarcity.RangelandshavebeensteadilyconvertedtodevelopedDroughtsareincreasinginfrequencyandduration.Waterandagriculturallanduses.Urbanizationisprojectedtobeshortageoccurswhendemandsarepartiallyorfullyunmet,responsibleformostofthefuturereductioninrangelandaconditionalsoreferredtoassocioeconomicdrought.Muchextent,especiallyinthePacificCoastRegion.oftheUnitedStatesexperiencedatleastmoderatewater2020ResourcesPlanningActAssessment1-7shortagesduringtheperiodof1986to2015.ThesouthernDroughtscanbecharacterizedbyhowoftentheyoccurandGreatPlainsandRockyMountainSubregions,southernhowlongtheylast.Bothshort-andlong-termdroughtsareCalifornia,andnorthernFloridaalreadyexperiencehigh-projectedtoincreaseinintensityanddurationinthesouthernintensityshortagesoflessthanamonthinlength,aswellGreatPlains,andshort-termdroughtsareprojectedtolastasrelativelylessintenseshortageswithdurationequaltoorlongerinthemiddleGreatPlains,Southwest,andSouth.greaterthan6consecutivemonths.Extremedroughtsthatmayberelativelyinfrequenttodayareprojectedtobecomemorefrequentbymid-century,Projectedchangesinnationalconsumptivewateruserangeespeciallyunderafuturewithhighatmosphericwarming.froma9-percentdecreasetoa235-percentincrease,withUnderthisfuture,droughtsthatlastlongerthan3yearsarethelargestimpactsresultingfromtheneedsofagricultureinprojectedtobemorethan19percentmoresevereonaverageresponsetoclimatechange.(whileshortagesincreaseby19percent),anddroughtslastingmorethan10yearsareprojectedtooccurabout6AcrossRPAscenariosandclimateprojections,changesintimesmoreoften.domesticwateruseareprojectedtorangefroma55-percentdecreasetoa2-percentincrease.DespiteprojecteddecreasesAdaptationoptionslikeincreasedreservoirstoragehaveinhouseholdwateruse,changesintotalconsumptivewaterlimitedabilitytocurtailshortageinthelongterm.Responsesuseareprojectedtorangefroma9-percentdecreasetoatoclimatechangewillprobablyrequiresubstantialtransfers235-percentincreaseby2070.Inmostplaces,increasesorfromagriculturetourbanusers,whichcouldhaveseriousdecreasesinwaterusedependonagriculture’sresponsenegativeimpactsonruralcommunities.tochangesinprecipitationandtemperature.Nationally,agricultureaccountsfor42percentoftotalwaterAswaterscarcityincreasesanddroughtsbecomemorewithdrawals,sochangesinagriculturalwaterusehavethefrequent,economicpressurewilllikelyshiftwateruselargestimpactonaggregatewateruse.Overthelastfewbetweensectorsandregions.Longertermresponsestodecades,irrigationpracticeshavebecomemoreefficient.climatechangemightrequiretransfersfromagriculturetoAcrosstheWesternUnitedStates,bothacresirrigatedandurbanusers,whichcouldhaveseriousnegativeimpactswaterappliedperacrehavefallen.IntheEast,however,onruralcommunities.Pastdroughts,aswellasincreasingirrigationhasbecomemorewidespreadtoensuremorecompetitionwithmunicipalwateruses,haveledsomereliablefarmyields.Futurewaterusedependsonwhetherfarmerstorelymoreongroundwaterthaninthepast.trendsintheEastcontinueandhowwesternfarmersrespondAquifersthroughoutthecountryarebeingdrawndowntodrierconditions,particularlyinthesouthernGreatPlains,atratesthatfarexceedtheirrechargerates.CommunitiesIntermountain,andPacificSouthwestSubregions,forwhichhavealsosoughttoincreasetheirreservoirstorage,whichresultsacrossclimateprojectionsarehighlyvaried.mightprovideshort-termrelief,butisoftencontentiousandultimatelyreliesonsufficientwateryieldtofilltheChangesinprojectedaggregatewateryieldbymid-centuryreservoirs,anincreasingproblemthroughouttheNation.rangefroma25.7-percentincreaseunderawetfuturetoaInareasthatrelyheavilyonhydroelectricpower,reservoir10.9-percentdecreaseunderadryfuture.levelsmaybecomelowenoughtoaffectpowergeneration.ClimatemodelprojectionsforprecipitationandwaterBiodiversity:yield(whichisstronglycorrelatedwithprecipitation)WildlifeandAquaticBiotaaremorevariedthanprojectionsfortemperature.TheRPAprojectionsassociatedwithadryfutureanticipateTrendsfrombreedingbirdsurveysindicatepopulationdecreasesinwateryieldintheSouth,Southeast,andGreatdeclinesinatleast20percentofallbirdspeciesacrosshabitatPlains,whereasincreasesinwateryieldareprojectedintypessincethe1950s/1960s,andinmorethan50percentofthesesameregionsunderwetandhotRPAfutures.Waterspeciesthatoccupygrasslandsoraregroundnesting.TheseyieldprojectionsconsistentlyincreaseforthemuchofthedeclinesarelinkedtolandusemodificationsofhabitatsasWesternUnitedStatesbutdecreaseintheSouthwest.Muchwellasintroducedspeciesandlossofhabitatconnectivity.warmertemperaturesintheSouthareprojectedtoincreasepotentialevapotranspirationmorethanforanyotherregion,Wildbirdpopulationshavelongbeenconsideredgoodamplifyingtheeffectsofdecreasedprecipitationandleadingindicatorsofenvironmentalthreatslikelandscapechangetofurtherdeclinesinwateryield.becausechangesinhabitataffecttheabundanceanddiversityofbirdspeciesthatoccupyaparticularregion.Inaddition,Short-durationdroughtsarelikelytoturnintolong-durationmanybirdspeciesarehighlymigratory,makingthemdroughts,andtheintensityofdroughtislikelytoincreasevulnerabletochangesinlanduseandclimateatdifferentsubstantially.Underhigherfutureatmosphericwarming,stagesoftheirlifecycleastheymoveamongenvironments,droughtslastingmorethanayearareprojectedtooccurfoursomeofwhichareoutsidetheUnitedStates.Populationtimesmoreoftenandincreaseinintensityby76percent.1-8FutureofAmerica’sForestsandRangelandsdeclinesandvariabilityoverlong-andshort-termtimechange:mountainsinthePacificCoast,RockyMountain,periodsreflectongoingstressonexistingavianfauna.DataandSouthRegions;largeareasfromNewYorktoMainefromlong-termbreedingbirdsurveysshowdeclinesinintheNorthRegion;andlowerelevationlandsinsouthernpopulationsizes.GrasslandbirdspecieshadthegreatestNewMexico,southernArizona,Oklahoma,andTexas.declinesinlong-termtrends,with54percentofspeciesTheconsistencyofhighstressintheseareassuggeststhatshowingsignificantdecreases,whileonly4percenthadwildlifemanagerswilllikelyseechangesinwildlifehabitatsignificantincreases.Severalcategoriesofharvestedbirds,andwildlifedistributions.Areasofhighelevationthroughoutincludingspeciesofgeeseandducks,haveremainedstablethePacificCoastandRockyMountainRegionsareprojectedoverthelong-term,butweblessmigratorybirds,includingtoexperiencehighstressundertheboththeRPAhotanddryAmericanwoodcockandmourningdove,areindecline.modelprojections.HigherelevationsintheeasternpartoftheconterminousUnitedStatesappeartoexperiencemoreConcentrationsofimperiledtaxawithalistingstatusunderstressunderhotprojectionsthandryprojections.theEndangeredSpeciesActarefoundacrossthecountry,withparticularconcerninPeninsularFloridaandHawaiiforFederallandswithalowerriskofdevelopmentorlandbirds,andintheRPANorthandSouthRegionsforfishes,conversion,suchasthosemanagedbytheNationalForestcrayfish,andmussels.SystemandU.S.NationalParkService,areprojectedtobeunderhigherclimatestresscomparedwithotherlands,IncreasingnumbersofspeciesacrosstaxaarebeinglistedpotentiallylimitingtheirfutureabilitytofunctionasclimateundertheEndangeredSpeciesAct,withfewspeciesdelistedrefugiafornativebiota.duetoconservation.CurrentpatternsofdistributionreflectcumulativecountsoffederallylistedimperiledspeciesoverNationalForestSystemandU.S.NationalParkServicelandstime.Concentrationsoffederallylistedimperiledtaxaarecontainmanyfederallylistedspecies,makingthemcriticalfoundacrossthecountry,withhotspotsinPeninsularFloridafortheprotectionandrecoveryofimperiledbiota.However,andHawaiiforbirds,andintheNorthandSouthRegionstheselandsareprojectedtoexperiencegreaterclimatestressforfishes,crayfish,andmussels.Amongforest-associatedthantherestofthecountryduetofactorssuchastheirspecies,thegreatestproportionofpossiblyextinctandat-locations,ofteninhigherelevations.Thus,climate-drivenriskspeciesisfoundamongamphibians.stressprojectedforFederallandsmaylimittheirfutureabilitytofunctionasrefugia.ThisbecomesparticularlyWatershedsoftheRPANorthandSouthRegionsaremostrelevantwhenlandusechangeprojectionsforprivatelandvulnerabletocompoundedlandusestress.RegardlessofacrossmuchofthecountryanticipatepermanentconversionRPAregion,developmentstandsoutasthelargestoveralltodevelopedlanduse.landusestressorfornativeecosystems.OutdoorRecreationLandusepressuresincludinglandconversion,humanandWildernesspopulationgrowth,expansionofagriculturalareas,anddevelopmentofenergyinfrastructureandminingaremostPubliclymanagedrecreationresources,atalllevelsofpronouncedinwatershedsoftheEasternUnitedStates,government,providemostopportunitiesforoutdoorspecificallytheRPANorthRegionandareasoftheSouthrecreation.Region,wherefewerFederallandsexisttofilltheroleofecologicalreserve.ManagersintheEastmaythereforefaceTherecreationopportunitiesofferedbygovernmentsvarymoreintenselandusepressuresthanintheWest,whereintheirtypes,naturalsettings,andlocationsrelativetoincreasedpressuresareassociatedwithpopulationandpopulationcenters.ForthoselivinginorvisitingurbanagriculturalcentersinWashington,Idaho,California,andandperi-urbanareas,localpubliclandsgenerallyofferthepocketsoftheRockyMountains.Thisspatialpatternvariesmost-accessiblespacesfornature-basedoutdoorrecreation.fromclimate-drivenstress,whichisgenerallyhighestintheLocalgovernmentpubliclandstypicallyofferopportunitiesNorthandPacificCoastRegions.toengageinthemost-popularoutdoorrecreationactivities,suchaswalking/hiking,viewingnatureandwildlife,andAreasofpotentialhighclimatestresswereconsistentlysimplyrelaxingintheoutdoors,andoftenaccommodatefoundinmountainousareasoftheRPANorth,Rockythosewithawiderangeofskillsandabilities.StateparkMountain,andPacificCoastRegions,withpocketsofstressagenciesandotherState-levelagenciesfocusedonforestry,identifiedinaridregionsoftheRockyMountainRegion.wildlife,landconservation,orothernaturalresourcesalsoprovidepublicrecreationopportunities.TherearemorethanClimatechangeisaffectingterrestrialandaquatichabitats2.2millionacresofStateparklandacrosstheUnitedStates.intheUnitedStates,resultinginlarge-scaleshiftsintheAmongRPAregions,theNorthRegionhasthegreatestrangeandabundanceofnativefauna.ProjectionsidentifiednumberofStateparkacres.SevenFederalagenciesprovideseveralareaswhereamajorityoftheplausiblefuturespredicthighstressfornativespeciesinresponsetoclimate2020ResourcesPlanningActAssessment1-9themajorityofrecreationopportunitiesonnearly400Greaterincomeandpopulationgrowthgenerallyresultinmillionacresoffederallymanagedlands.Ingeneral,Federalhigherratesofpercapitaparticipationinoutdoorrecreation.landsaremostcommonintheWestbutarepresentineveryRPAregion.PrivatelandsarelessaccessibleandmostModestchanges(frequentlydeclines)inpercapitaopportunitiesontheselandsaccruetolandowners.participationratesinoutdoorrecreationareprojectedforthecomingdecades.Ingeneral,projectedpercapitaPercapitaparticipationinoutdoorrecreationactivitieshasparticipationisgreaterunderRPAscenariosthatassumethebeenrelativelystableinrecentyearsbutpopulationgrowthhighestincomegrowth.Theexceptionstothatpatternarehasledtoanincreaseinthenumberofparticipants.hunting,motorizedoff-roadrecreation,anddevelopedsitecamping,whereprojectedpercapitaparticipationislowestAbout50percentoftheU.S.populationengagesinoutdoorunderthehighestratesofincomeandpopulationgrowth.recreation.ThatparticipationratehasremainedstablesinceThegreatestnumbersofparticipantsareprojectedunderthe2007,beforeincreasingtoabout54percentofthepopulationhighestincomeandpopulationgrowthRPAscenariosforin2020.Oftheactivitiescommonlyassociatedwithforests,almostallactivitiesandforallRPAregions.Inmanycases,rangelands,andotheropenspaces,hiking,camping,andthehighratesofpopulationgrowthintheRPAscenariosfreshwaterfishingareconsistentlythemost-popular,withoverwhelmanyprojecteddeclinesinpercapitaparticipationbetween13and15percentofthepopulationengaginginthoserates,increasingthetotalnumberofparticipants.Thisisactivities.Before2020,participationhadbeenincreasingespeciallytrueinregionsliketheRPASouth,whereweslightlyforhiking,decliningforcamping,andremainingprojectlargepopulationgainsinfuturedecades.steadyforfishing.Althoughparticipationrateshavebeenmostlysteady,thenumberofoutdoorrecreationparticipantsContinuedpopulationgrowthresultsinagreaternumberofhasincreasedwithagrowingU.S.population.Between2008outdoorrecreationparticipants,evenpotentiallyoffsettingand2018,anadditional15millionpeopleengagedinoutdooranydeclinesinpercapitaparticipation.recreation,withmostofthatincreaseattributedtohiking,whichhadanetincreaseof18millionparticipants.ThenumberofparticipantsengaginginarecreationactivityinthefuturereflectsbothchangesinpercapitaForestrecreationresourceavailabilitypercapitaisexpectedparticipationovertimeandthesizeofthefuturepopulation.tocontinuetodeclineinfuturedecadesforlocationsAlthoughtheremaybemeaningfulchanges(increasesorexperiencingpopulationgrowth.decreases)inpercapitaparticipationandaveragenumberofdaysofengagementforindividualactivities(theperDeclinesinthepercapitaavailabilityofforestsforrecreationcapitaconsumptionmeasureforrecreation),populationareprojectedundermoderateandhighlevelsoffuturegrowthtypicallymagnifies(forincreases)oroffsets(foreconomicandpopulationgrowth.IntheseRPAscenarios,decreases)thosechanges.Projectednationalandregionalprojectedlossesinpercapitanon-FederalforestareaarefoundlossesinthenumbersofparticipantsengaginginactivitiesineveryRPAregionandaremostsignificantinthefarnorthin2040and2070relativeto2012areprimarilyconfinedoftheNorthRegion,thenorthernportionsofthePacificCoasttothehighwarming-lowU.S.growthRPAscenario(HL).Region,andthesouthernportionsoftheRockyMountainPotentialdeclinesinthenumbersofparticipantsin2040andRegion.Somegainsinpercapitanon-Federalforestrecreation2070extendintothehighwarming-moderateU.S.growthareaareprojectedunderscenarioswithlowerfutureeconomicscenario(HM)nationallyandforseveralregionsforhunting,andpopulationgrowth.Whengainsareprojectedtooccur,motorizedsnowuse,cross-countryskiingandsnowshoeing,theyaremostcommoninthenorthernareasoftheNorthandandfloating.ProjecteddeclinesinparticipationforhuntingRockyMountainRegions.Federalforestrecreationareahasextendintothehighwarming-highU.S.growthscenariobeengenerallystableoverthelastseveraldecadesandisnot(HH)intheRPANorthRegion,reflectingthesteepprojectedprojectedtogrowsubstantially.Inthepresenceofcontinueddeclineinpercapitahuntingparticipationinthefaceofpopulationgrowth,however,percapitaareaofFederalbothhighatmosphericwarmingandstrongpopulationandforestsisprojectedtodecline.Likewise,theareaofState-economicgrowth.managedforestsintheUnitedStateshasremainedsteadyinrecentyearsandisnotexpectedtogrow.TherehavebeensomegainsinthesizeofU.S.Stateparksystemsinrecentyears,butmostofthosegainsappeartotracetoadministrativechangesamongStateagenciesratherthanexpansionoftheareaunderStateownership.1-10FutureofAmerica’sForestsandRangelandsGreateratmosphericwarmingisprojectedtohaveanegativeinfluenceonrecreationengagementinmanyactivitiesandlittlepositiveinfluence.Participationratesin6of17activitiesexhibitedmarkedresponsivenesstotheleveloffutureatmosphericwarming.Inallcases,futureclimaticchange,asinfluencedbyincreasinglevelsofatmosphericwarming,ledtolowerparticipationratesandreductionsintheaveragenumberoftimeseachyearthatpeoplerecreateacrossallclimatefutures.Motorizedsnowuseandcross-countryskiingandsnowshoeingweretheactivitiesthatexhibitedthegreatestnegativeresponsetohigheratmosphericwarming.WithintheRPAscenariosandtheirassociatedassumedlevelofatmosphericwarming,thespecificRPAclimateprojectionsalsoinfluencedparticipationinoutdoorrecreationinmanyactivities.Whenuniquepatternswerepresent,theymostfrequentlyoccurredforthehot,dry,andleastwarmclimatefutures.Althoughthereisgenerallyalotofvariabilityacrosstheactivities,hotanddryclimatefuturestendtoyieldlowerparticipationrates,whiletheleastwarmclimatefuturetendstoyieldhigherparticipationrates.Projectionsofconsumption,measuredasannualdaysofrecreation,showincreasesacrossmostactivities,withthegreatestnumbersofrecreationdaysinactivitiesofageneralorbroadlyaccessiblenature,i.e.,dayhiking,viewingnature,developedsiteuse,anddevelopedsitecamping.Continuedgrowthisprojectedinthetotalnumberofdaysofengagementannuallyinoutdoorrecreation.Growthindaysofengagementisprojecteddespiteprojecteddeclinesintheaveragenumberofdaysthateachparticipantrecreates.Theprojectedgrowthindaysofrecreationislargelydeterminedbythemagnitudeofprojectedpopulationincrease,andthusthenumberofpotentialrecreationists.Foralmostallactivities,theprojectedgrowthinthenumberofrecreationparticipantsoverwhelmsanyprojectedchangesintheaveragenumberofdaysspentrecreatingperparticipant.Totaldaysofengagementinoutdoorrecreationactivitiesarethereforeprojectedtobegreatestwhenprojectedpopulationisgreatest.Dayhiking,viewingnature,developedsiteuse,anddevelopedsitecampingareprojectedtoaccountforthegreatestnumbersofdaysofrecreationinfuturedecades,consistentwithcurrentpatterns.2020ResourcesPlanningActAssessment1-11Chapter2IntroductionU.S.DepartmentofAgriculture,ForestService.2023.Introduction.In:U.S.DepartmentofAgriculture,ForestService.2023.FutureofAmerica’sForestandRangelands:ForestService2020ResourcesPlanningActAssessment.Gen.Tech.Rep.WO-102.Washington,DC:2-1–2-7.Chapter2.https://doi.org/10.2737/WO-GTR-102-Chap2.The2020ResourcesPlanningAct(RPA)AssessmentisScopeoftheAnalysisthesixthreportpreparedinresponsetothemandateinthe1974ForestandRangelandRenewableResourcesTheRPAAssessmentreportsonabodyoftargetedresearchPlanningAct(P.L.93-378,88Stat475,asamended),whichfundedbytheUSDAForestServicetoaddresstheRPArequirestheSecretaryofAgriculturetoassesstheNation’slegislativemandate,providingbothhistoricaltrendsandrenewableresourcesevery10years.TheRPAAssessmentisprojectingplausiblefuturesofforestandrangelandresources.intendedtoprovidereliableinformationonthestatus,trends,Basedonanunderstandingofthehistoricaltrends,ourandprojectedfutureoftheNation’srenewablenaturalresearchfocusesonanalyzingtheinfluencesofmultipleresourcesonallforestsandrangelandsona10-yearcycle.driversofchangeonrenewablenaturalresources50yearsintoWhilenotrequiredbytheauthorizinglegislation,theU.S.thefuture,withthegoalofinformingandenablingplanningDepartmentofAgriculture,ForestServicealsopreparesmid-topreventfutureresourcedegradationandshortage.ThecycleupdatestodecadalRPAAssessments.The2020RPAanalysesintheRPAAssessmentrespondtothemandatedAssessmentfocusesonpast,current,andprojectedfuturenationalall-landsfocusandincluderenewablenaturalavailabilityandconditionofforests,forestproductmarkets,resourcesandrelatedeconomicsectorsforwhichtheUSDArangelands,water,biodiversity,andoutdoorrecreation,asForestServicehasmanagementresponsibilities:forests,wellastheeffectsofsocioeconomicandclimaticchangeforestproducts,rangelands,water,biodiversity,andoutdoorupontheseresources.recreation.WeexaminepotentialdirectandindirecteffectsofsocioeconomicandclimaticchangeonfutureresourceTheRPAlegislationrecognizestheimportanceofourforeststrendsbyincorporatingdemographic,economic,andclimaticandrangelandsincontributingtotheAmericanpublic’swell-variablesintoourmodels.Wecontinuetotargetourresearchbeingandqualityoflife.TheAmericanpubliccontinuestotoimproveunderstandingofthemultipleandinteractingdependonourforestsandrangelandstoprovideavarietyfactorsthatweexpecttoaffectrenewablenaturalresourcesofecosystemservices.Maintainingproductiveforestsandthroughacoherentandintegratedviewofthefuture.rangelandsrequirescontinualmonitoringandanalysisoftheeffectsofchangingsocialexpectationsandachangingWecapitalizeonareaswheretheUSDAForestServicehasclimateontheseresources.TheRPAAssessmentimprovesresearchcapacity.TheRPAAssessmentdrawsupontheourunderstandingofthemultipleandinteractingfactorsthatexpertiseofotherFederalagenciesthathaveresponsibilitiesweexpecttoaffectrenewablenaturalresourcesinthefuture.fornationalanalysesbyusingtheirdataandincorporatingThisfocusisauniquecontributionthatprovidesimportanttheirreportsbyreference.Forexample,werelyoninformationtopolicymakersandresourcemanagersastheyinformationfromtheU.S.EnvironmentalProtectionAgencydevelopstrategiesforsustainingtheNation’srenewableaboutwaterquality.Likewise,wedonotanalyzerenewablenaturalresources.Thischapterprovidesanoverviewoftheenergy,withtheexceptionofwood-basedbioenergy,because2020RPAAssessment,describingthescopeofRPAanalysis,theU.S.DepartmentofEnergyconductscomprehensivethedocumentorganization,andtheframingcontextfortheanalysesoftheenergysector.WealsodrawupontheworkofAssessment.ourresearchandtechnologypartnersintheuniversitysector,whoareacknowledgedandheavilycitedthroughouttheAssessment.2020ResourcesPlanningActAssessment2-1Ouranalysestypicallyhaveanationalfocus,whichTheselectionofEnglishversusmetricunitsinreportingrequireseithernationallyconsistentdataordatathatcanRPAresultscontinuestobechallenging.Whilescientificbeconsistentlycompiledtothenationallevel.Thenationaloutletsareprimarilyinmetricunits,EnglishunitsarestillfocusoftencreatesdataconstraintsthatlimitanalysescommonlyusedinU.S.discussionsandanalyses.Asaresult,insomeresourceareasandoftenrestrictanalysestothewehavetakenahybridapproachinthisAssessmenttoconterminousUnitedStates.Forsomeresourceareas,followstandardconventions.Metricunitsareusedinmanyanalysesareconductedatasubnationalgeographicextenttochaptersbecausemetrichasbecomethepredominantunitreflectthegeographicextentoftheresource.Forexample,inbothtechnicalandpolicydiscussions(i.e.,Disturbance,ourrangelandanalysesfocusontheWesternUnitedStates,ForestProducts,RangelandResources,Biodiversity),whilewheremostrangelandisfound.TheresultsoftheanalysesotherchaptersprovideEnglishunitsbecauseofcommonthroughoutthesubsequentchaptersoftenwillbepresentedusageintheUnitedStates(i.e.,LandResources,OutdoorforboththeentireUnitedStatesandforthefourRPARecreation).BothsetsofunitsareusedintheForestAssessmentregions(figure2-1).OtherregionaldefinitionsResourcesandWaterResourcesChapters:Englishunitsareareusedforspecificresourceanalysesandaredescribedinusedforforestareaandvolumereportingandwateruseduetheresourcechapters.tocommonusageamongU.S.audiences,whilemetricunitsareusedforcarbonaccountingandwateryieldtomaintainWhiletheRPAAssessmentfocusesprimarilyonnationalconsistencywiththescientificcommunityandinternationalanalyses,thedatasupportingtheseanalysesareavailableatreporting.WehaveprovidedresultsinbothEnglishandvaryingspatialresolutions,and,therefore,thegeographicmetricunitsintheConclusionssectionofeachchaptertoscaleofourresultsalsovaries.Asaresult,terminologymeettheneedsofallaudiences.aboutthe“scale”oftheanalysescanbeconfusing,especiallybecausescaleisdefineddifferentlyacrossdisciplines.IntheDocumentOrganizationabsenceofauniversaldefinition,wehavetriedtoclearlydefinethecontextforscaleintheseanalysesbyspecifyingPrecedingthisintroduction,the2020RPAAssessmentkeywhenwearereferringtoextent,resolution,orsomeotherfindingsarepresentedbyindividualresourcetopic(theKeycharacteristicofscale.Findingsofthe2020RPAAssessmentChapter).Followingthisintroduction,wedescribethefuturescenariosusedasFigure2-1.RPAAssessmentregionsandsubregions.2-2FutureofAmerica’sForestsandRangelandsthebasisforthe2020RPAAssessmentprojections(theinthe2010RPAAssessment,thecurrentAssessmentusesScenariosChapter).Theremainingchapterspresentresultsascenarioapproachtoprojectresourcefuturesbasedonbyresourceareaorresourcesectorandincludebothchaptertheanticipatedeffectsofchangesinpopulationandincomeandsectionkeyfindings.(availableatthecountyscale)andclimate(availableata4-km2scale)onforestsandrangelands.WeconstructTheinformationpresentedinthesechaptersbeginswitharangeofscenariosbycombiningassumptionsabouthistoricalinformationthatistrackedacrossRPAAssessmentourkeydrivers(seetheScenariosChapter)andprovidereportingcycles.Changesinhistoricaltrendsareofguidanceontheirapplication(seetheScenariosChapter,particularinterestbecausefutureprojectionsareinfluencedthesidebarUsingScenariosandProjectionsinResourcebyhistoricaltrends.Futureresourceconditions,demand,andManagementPlanning).Forcontext,thefollowingprovidessupplyareprojectedfor50years(2020to2070inthisRPAabriefoverviewofrecentglobalandnationalpopulation,Assessmentcycle)forthoseresourcesforwhichsufficienteconomic,andclimatictrends,aswellasglobaltrendsindatawereavailable.TheRPAanalysestypicallyassumethatforestandrangelandarea—nationaltrendsinforestandpoliciesaffectingresourceconditionsremainconsistentoverrangelandareaarecoveredindepthintheLandResources,theprojectionperiod.ThisassumptionismorechallenginginForestResources,andRangelandResourcesChapters.thescenarioframeworkusedforthe2020RPAAssessment,especiallygiveninternationaleffortstoaddressclimatePopulationGrowthchangeeffects.AsdescribedintheScenariosChapter,jointlyachievingclimateandsocioeconomicfuturesmayrequireGlobalpopulationgrewfrom6.9billionin2010to7.7policyortechnologychanges,althoughthemeansmayvarybillionin2019andisprojectedtoreachapproximately10.5widelyacrosslocal,national,andglobalscales.Individualbillionby2070(UnitedNations2019a).Thepercentageofresourceanalyseswilladdresswhethersignificantchangestheglobalpopulationlivinginurbanareaswas55percentininsocioeconomicandclimaticdriversarelikelytoshift2018,upfrom30percentin1950(UnitedNations2019b).resourcetrajectories.EstimatesandprojectionsofglobalurbanizationindicatethatthegrowingnumberofcitydwellersmayaccountforThisdocumentsummarizestheresultsofanalysesthatarealmosttheentirefuturegrowthofthehumanpopulation.documentedinmoredetailinaseriesoftechnicalsupportingTheUnitedNationsprojectsthat68percentoftheworld’sdocumentsreferencedthroughoutthechaptersthatfollow.populationwillbelivinginurbanareasby2050(UnitedThesesupportingdocumentsprovidemoredetailsondata,Nations2019b).methods,andresults.RPAAssessmentsupportingtechnicaldocumentsareavailableontheUSDAForestService’sRPAUnlikemanyhigh-income(percapita)countrieswhereAssessmentwebpageastheybecomeavailable:https://populationisdeclining,theU.S.populationcontinuestowww.fs.usda.gov/research/inventory/rpaa.increase.The2020CensusindicatedthattheU.S.populationincreased6.3percentbetween2010and2020(slowerthanFramingContextthealmost10-percentincreasebetween2000and2010),exceeding328millionin2019.AlthoughtheU.S.populationPopulation,income,andclimaticfactorsareallkeydriverscontinuestogrow,itdidsoattheslowestratesincetheofresourcedemandsthataffectthefuturestatusofforests1930s;theU.S.annualrateofpopulationgrowthdroppedandrangelands—increasingpopulationandpercapitafrom0.73percentin2011to0.50percentin2020(USCBincomehavebeenshowntoincreasedemandforgoods2021a),ratesconsistentwithlownet-immigration(USCBandservices,ashavechangingclimaticfactorsincluding2021b).RegionalpopulationgrowthwasfasterintheSouthincreasingtemperatures.ChangesinclimatecanalsoaffectandWestthanintheMidwestandNortheast.Overall,thethefutureconditionandsupplyofresources,withprofoundSouthandWestaccountedformorethan80percentofandhighlyvariableimpactsonforestandrangelandtheU.S.populationincrease.TheStateswiththehighestresources.Notonlyistheeffectofclimatechangeonnumericincreaseswere,indescendingorder,Texas,Florida,temperatureandprecipitationprojectedtobevariableacrossCalifornia,Georgia,Washington,andNorthCarolina.ThesetheUnitedStates,butindividualresourcesareprojectedsixStatesaccountedforapproximatelyhalfoftheoveralltoresponddifferentlytochangesinclimate.Thechangingincreaseinthelastdecade.climatewilllikelybenefitsomeecosystems,species,andassociatedgoodsandservicesattheexpenseofothers.Eighty-sixpercentoftheU.S.populationin2020livedinametropolitanstatisticalarea,andpopulationintheseareasItisthereforeimportanttocomparetheplausiblefuturegrewatafasterrate(9percent)thantheoverallU.S.rateconditionandavailabilityofforestandrangelandsresources(USCB2021c).The2020Censusdataonurbanareaswereunderthechangingclimatewithplausiblefuturedemandtonotyetavailable;however,thegrowthinpopulationinidentifypotentialfutureshortagesofimportantforestandmetropolitanstatisticalareaswilllikelybemirroredbygrowthrangelandresources.Followingtheprecedentestablishedinurbanareas.2020ResourcesPlanningActAssessment2-3AlthoughtheSouthandWesthadthelargestincreasesendedthedecadewithhistoriclowsinunemployment.inpopulation,theU.S.populationisstillconcentratedWagegrowthwasslowformostofthedecade,leadingtoonthetwocoasts.AndwhileonlythreeStates—Illinois,ariseinwealthinequalityasthestockmarketcontinuedtoMississippi,andWestVirginia—lostpopulationinthelastrise.ThearrivalofCOVID-19in2020broughtaboutthedecade,depopulationoccurredinmorethanhalfofU.S.sharpesteconomicshocktotheU.S.economysincethecounties,continuingdecadesofpopulationlossinareasGreatDepression.Therecessionwastheshortestonrecord,suchasAppalachiancountiesineasternKentuckyandat2months,andU.S.realGDPexceededitspre-COVIDWestVirginia,manyGreatPlainscounties,andagroupoflevelbythesecondquarterof2021(USDCBureauofcountiesaroundtheMississippiDelta.ManycountiesalongEconomicAnalysis2021).Unemployment,whichpeakedattheGreatLakesandtheNorthernU.S.bordereitherlostalmost15percentinApril2020,proceededtosteadilyfall,populationorgrewatverylowrates(USCB2021c).reachingpre-COVID-19levelsagaininApril2022(USBLS2022).ThearrivalofCOVID-19variants,ongoingproductEconomicOutlooksupplychaindisruptions,andtheneedforglobalvaccinedeploymenttobringanendtothepandemicproduce,attheTheglobaleconomyhasgonethroughconsiderablechangetimingofthiswriting,anuncertainshort-runfuturefortheduringthelastseveraldecades.The1970ssawoilpriceUnitedStatesandtheworld.shocks;the1980swereatimeofgeneraldeflationofcommodityprices;the1990ssawmanyhigh-income(perClimatecapita)countries,includingtheUnitedStates,shiftingfromindustrialtoservicesectors;andthe2000sincludedGlobally,eachdecadesince1980hasbeensuccessivelyaglobalrecessionthathadmajoreffectsontheglobalandwarmerthantheprecedingdecade,withthemostrecentU.S.economy,especiallyintherealestateandhousingdecade(2010s)beingaround0.36degreesFahrenheit(0.2constructionsectors.Thedecadeof2010to2020sawdegreesCelsius)warmerthanthepreviousdecade(2000s)gradualeconomicgrowthfromthenadirofthe2007to(BlundenandArndt2020).The2010swasthewarmest2009recession,withincreasingglobalsovereigndebtanddecadeonrecordfortheplanet,withasurfaceglobalconsistentlylowinflation,aswellasrisingincomeinequalitytemperatureof+1.48°F(0.82°C)abovethe20th-centurywithinmosthigh-incomecountriesoccurringalongsideaverage.Thecombinedlandandoceantemperaturehasdecreasinginequalitybetweencountries(UnitedNationsincreasedatanaveragerateof0.13°F(0.08°C)perdecade2020;WorldBank2016).since1880;however,theaveragerateofincreasesince1981hasbeenmorethantwicethatrate(0.32°F/0.18°C)Globalgrossdomesticproduct(GDP)increased24percent(NOAA2021a).The10warmestyearsinthe1880to2020between2010and2020,from$66.2to$81.9trillionrecordhavealloccurredsince2005,with7ofthewarmest(constant2010USD)(WorldBank2021).TherateofGDPyearsoccurringsince2014.Inaddition,hotextremeeventsgrowthinhigh-incomecountrieswasoutpacedbythesuchasheatwaveshaveincreasedinfrequencyandintensityrateobservedinemergingmarkets,ledbybutnotlimitedovermostlandareasincethe1950s.AlthoughwarmingtoChina.Globalcommoditytradeheldsteadyasasharehasnotbeenuniformacrosstheplanet,theupwardtrendinofglobalGDPuntiltheendofthedecade,whenseveralthegloballyaveragedtemperatureshowsthatmoreareascountriesenactedhighertariffs,withdrewfromexistingarewarmingthancooling.Globalimpactsofthiswarmingandproposednewtradeagreements,andotherwisetookincludeshrinkingarcticsummerseaice,thawingpermafrost,stepstolimitcross-borderflowsofselectedcommodities.increasingsealevelrise,andthealterationofgeographicalThearrivalofCOVID-19attheendofthefirstquarterofrangesandlifecyclesofmanyplantandanimalspecies.Total2020intheUnitedStatesandmanyothernationsbroughtannualprecipitationoverlandareasworldwidehasincreasedaboutasharpcontractionoftheglobaleconomy.Whileatanaveragerateof0.1inchesperdecadesince1901thiscontractionwasworsethanthe2007to2009financial(BlundenandArndt2020)andheavyprecipitationeventshavecrisis,growthreturnedmorequicklyduetofiscalsupportinbecomemorefrequentandintensifiedoverthegloballandafewlargeeconomiesandthedevelopmentanddistributionareawheredataareavailable(IPCC2021);however,becauseofvaccines(InternationalMonetaryFund2021).Centralhighertemperaturesleadtomoreevaporation,increasedwaterbankactionstofightinflationintheUnitedStatesandotherstressonplants,andhigherwaterusebypeople,increasedeconomies,geopoliticaluncertainty,andcontinuedsupply-precipitationwilloftennotincreasetheamountofavailablechaindisruptionsmakeitdifficulttoprojectthefutureglobalwater,especiallyatcriticaltimes(BlundenandArndt2020).economictrajectory.Aswithwarmingtrends,precipitationtrendshavealsonotbeenuniformacrosstheplanet.Forexample,agriculturalandTheU.S.economyinthe2010s,growingoutoftherecessionecologicaldroughtinwesternNorthAmericahasincreasedthatbeganattheendof2007,experiencedthefirstrecession-sincethe1950s(IPCC2021).freedecadesincerecord-keepingbeganinthe1850sand2-4FutureofAmerica’sForestsandRangelandsBasedona126-yearrecord,theaverageannualtemperatureTherateofglobaldeforestationremainssubstantialbutfortheconterminousUnitedStatesisincreasingatancontinuestoshowsignsofdecreasing,from12.8millionaveragerateof0.16°F(0.09°C)perdecade—theincreaseacresofforestlostperyearduringthe2000sto11.6millionrisestoanaveragerateof0.48°F(0.27°C)perdecadeacresperyearduringthe2010s.Thelargestnetlosseswhenexaminingtemperaturessince1970(BlundenandoccurredinAfrica,wheretherateoflossincreasedfromtheBoyer2020).TheaverageannualtemperatureforAlaskahaspreviousdecade,followedbySouthAmerica,wheretherateincreasedatahigheraveragerateof0.31°F(0.17°C)peroflossinthe2010sdeclinedby50percent.Deforestationdecadeoverthe96-yearrecord—withtheincreaserisingtoresultsinthelossofecosystemservicesprovidedbyforests,anaveragerateof0.90°F(0.50°C)perdecadesince1970.includingtheprovisionoffood,fuel,andfiber;carbonNineofNorthAmerica’s10warmestyearshaveoccurredstorage;floodanderosioncontrol;andopportunitiesforsince2001,withtheyear2016beingwarmestyearonrecordrecreationandculturalenrichment.Large-scaleplantingwithatemperaturedepartureof+3.46°F(1.92°C).ForoftreesissignificantlyreducingthenetlossofforestareatheconterminousUnitedStates,2021rankedasthefourth-globally,throughacombinationofafforestationandnaturalwarmestyearinaverageannualtemperatureinthe127-yearexpansionofforest.Asiahadthehighestnetgainofforestrecord,withthesixwarmestyearshavingalloccurredsinceareafrom2010to2020,althoughtherateofgaindeclined2012(NOAA2022).MaineandNewHampshirehadtheirfromthepreviousdecade.Theareaofplantedforestsecond-warmestyearonrecordin2021(NOAA2022),whilecontinuestoincrease,albeitatadecreasingrate,accounting10StatesacrosstheSouthwest,Southeast,andEastCoastfor7percentoftotalglobalforestarea(FAO2020).hadtheirsecond-warmestyearonrecordin2020.Noareasobservedbelow-averageannualtemperatures(NOAA2021b).Rangelands—definedintheRangelandsAtlasaslandonAnnualaverageprecipitationhasincreasedby4percentwhichthevegetationispredominantlygrasses,grass-likeacrosstheUnitedStatessince1901,withstrongregionalplants,andforbsorshrubsthataregrazedorhavethepotentialdifferences,includingincreasesovertheNortheast,Midwest,tobegrazedbylivestockandwildlife—cover54percentofandGreatPlainsanddecreasesoverpartsoftheSouthwesttheworld’slandsurface(ILRI2021).RangelandsarefoundandSoutheast(Easterlingetal.2017).Alaskashowslittleineveryregionoftheworldandprovideavarietyofserviceschangeinannualprecipitation(+1.5percent),whileHawaiiincludingprovidingwildlifehabitat,storingcarbon,andshowsadeclineinannualprecipitationofmorethan15supportinglargeriversandwetlands.Rangelandsaroundpercent(Easterlingetal.2017).Inanygivenyearbetweentheworldarecurrentlyexperiencingthreatsfromboth1895and2010,around14percentoftheNationexperienceddevelopmentandclimatechange(ILRI2021).moderatetoseveredrought,onaverage(Hayesetal.2012).ThethreelongestdroughtepisodesintheUnitedStatesTheUnitedNationshasprojectedthat70percentmorefoodoccurredinthe1930s,the1950s,andtheearly21stcentury.needstobegrownby2050tosupportthegrowingworldThemostrecentdrought,duringtheearly21stcentury,population(FAO2011).ThisgrowingdemandwillcontinuestartedinindividualregionsacrosstheconterminousUnitedtoputpressureonforestandrangelands,bothdomesticallyStates.BySeptember2012,two-thirdsoftheconterminousandglobally.UnitedStateswasindrought,withthedroughtnotbreakinguntil2014(Heim2017).Acrossmostofthecountry,heavyUncertaintyandtheCaseforScenariosprecipitationextremeeventshaveincreasedinbothintensityandfrequencysince1901,withthelargestincreasesoccurringInthechaptersthatfollow,wedescribehistoricaltrendsintheNortheast(Easterlingetal.2017).inresourceconditionsanduse.Aswelooktothefuture,uncertaintiesindemography,economics,andclimate—andForestsandRangelandsthepotentiallywide-rangingeffectsonnaturalresources—underpintheneedtoprojectalternativeplausiblefuturesTheFoodandAgricultureOrganization(FAO)estimatesusingascenario-basedstructure.Here,wereviewtheglobalforestareatobeabout10billionacres,coveringsourcesoftheseuncertaintiesandoutlinethejustificationfor31percentofthetotalgloballandarea(FAO2020).TheouruseofscenariosinprojectingthefutureavailabilityandFAOforestareaestimateisprimarilyrelatedtolanduse,conditionoftheNation’srenewableresources.meaningthatanareawithouttreesmaybeconsideredforest,whileagriculturalandurbanareaswithtreecovermaybeBeforethe2010RPAAssessment,theUnitedStatesandtheconsideredaslandusesotherthanforest.Thefivemostworldhadbeenexperiencinggrowingtradeliberalizationforest-richcountries,indescendingorder,aretheRussianasaresultofrepeatedroundsofGeneralAgreementonFederation,Brazil,Canada,theUnitedStates,andChina.TariffsandTrade/WorldTradeOrganizationagreements.TheThesecountriesaccountformorethanhalf(54percent)ofUnitedStatesandtheworldthenexperiencedtwoglobalthetotalglobalforestarea.U.S.forestlandaccountsfor7.6recessions:2007to2009and2020.Growingtradefrictionspercentoftheworld’sforestarea.amongtheworld’slargesttradingnationsandblocsoccurredinthe2010s,andcollectionsofcountrieshadincomplete2020ResourcesPlanningActAssessment2-5successestablishinginclusiveplurilateralagreementssuchrelativecomparativeadvantageoftheU.S.forestproductsastheTrans-PacificPartnership.Worldinvestorsalteredsectorandraisetheattractivenessofforestsasalanduse.theirbehaviorinthelastdecade,reducingforeigndirectinvestment,withimplicationsfortradeandmanufacturing.GiventherecentvariabilityineconomicandclimaticvariablesIncontrast,theUnitedStatesexperiencedincreasedforeignandtheuncertaintiessurroundingtheirfuturedevelopment,investmentinthewoodproductssectoroverthepastdecade,weuseasetofscenariostoprojectalternativeplausiblenotablyintheU.S.South,fortheproductionoflumberandfutures(seetheScenariosChapter);thosefuturesarestronglywoodpelletsforenergy.influencedbypopulationandeconomicassumptions,alongwithprojectionsoffutureclimatechange.ScenariosarenotLayeredovertheuncertainnationalandglobalenvironmentsassignedlikelihoods,norareanyscenariosintendedtobeanddecliningtradegrowthoverthepast10yearsare“accurate”perse.Rather,theseconstructedscenariosprovidetheincreasingeffectsofclimatechange.The2016ParisameansofqualitativelyandquantitativelyunderstandingAgreement—alegallybindinginternationaltreatythatsetshowarangeofsocioeconomicandclimateconditionsoutaframeworktoavoidglobalclimatechange,includinginteractthroughtimetocreatedifferentnaturalresourcetheroleofforests—affectshowpolicymakersandotherfutures.Globaland,inmostscenarios,U.S.populationsaredecisionmakersseeandmanageforests(UnitedNationsprojectedtocontinueincreasinginthefuture.TheoutlookFrameworkConventiononClimateChange2015).Inforeconomicgrowthismoreuncertain,particularlyinthediscussionsandnegotiationsfollowingthe2016Parisshortterm,butthelongertermgrowthtrendisexpectedtobeAgreement,forest-sectoractorsareconsideringhowforestspositive,althoughgenerallyslowerthaninrecentdecades.canmitigateclimatechangethroughbothactivemanagementInequality—whichhasbeenlinkedtorapidtechnologicalandtheuseofwoodtoproduceenergyandsubstitutesforchange,urbanizationandmigration,andclimatechange—morecarbon-intensivebuildingmaterials,aswellashowcaneitherrisewiththesetrendsorfalliftheyareharnessedforestsaredirectlyaffectedbyclimate-changeprocesses.tofosteramoresustainableworld(UnitedNations2020).Inthelattercategory,forestsareincreasinglythreatenedbyTheRPAAssessmentoutlookforU.S.resourcesisbasedonalteredratesandintensitiesofcatastrophicdisturbances.scenarioswithvaryingassumptionsaboutglobaleconomicThesedeleteriouseffectsofclimatechangecarrywiththemgrowth,globalwoodenergyconsumption,forestproductspossibleimpactsontheprovisionofmanyecosystemgoodstrade,domesticpopulationandeconomicgrowth,andglobalandservices(includingwaterqualityandquantity,recreationclimatechange.Ouranalysesindicatetheimportanceoftheseopportunities,wildlifehabitatprovision),thecostsoffactorsinassessingthealternativeresourcefuturesandmanagingforest-basedinsectanddiseaseepidemics,andthelikelychallengesforfuturerenewableresourcemanagement.challengesofmaintainingandgrowinghealthyurbanforests.ManagersandpolicymakerscanthereforeapplyourClimatechangemayalsobecontributingtoacceleratedfindingstoevaluatepotentialwaysofreducingthelikelihoodnetgrowthoftimber,whichcanbenefittimbergrowersofunwantedfuturesandincreasingthechancesforandwoodproductmanufacturers,potentiallyimprovethedesiredfutures.2-6FutureofAmerica’sForestsandRangelandsLiteratureCitedNOAANationalCentersforEnvironmentalInformation.2021b.Stateoftheclimate:nationalclimatereportforannual2020.https://www.ncdc.​Blunden,J.;Arndt,D.S.,eds.2020.Stateoftheclimatein2019.Bulletinnoaa.gov/sotc/national/202013.(10September2021).oftheAmericanMeteorologicalSociety.101(8):S1–S429.https://doi.org/10.1175/2020BAMSStateoftheClimate.1.NOAANationalCentersforEnvironmentalInformation.2022.Stateoftheclimate:Nationalclimatereportforannual2022.https://www.ncei.Blunden,J.;Boyer,T.,eds.2020.Stateoftheclimatein2020.Bulletinnoaa.gov/access/monitoring/monthly-report/national/202113.(15MayoftheAmericanMeteorologicalSociety.102(8):S1–S475.https://doi.2022).org/10.1175/2021BAMSStateoftheClimate.1.U.S.BureauofLaborStatistics[USBLS].2022(May6).TheEasterling,D.R.;Kunkel,K.E.;Arnold,J.R.;Knutson,T.;LeGrande,employmentsituation–April2022.https://www.bls.gov/news.release/A.N.;Leung,L.R.;Vose,R.S.;Waliser,D.E.;Wehner,M.F.2017.pdf/empsit.pdf.(15May2022).PrecipitationchangeintheUnitedStates.In:Wuebbles,D.J.;Fahey,D.W.;Hibbard,K.A.;Dokken,D.J.;Stewart,B.C.;Maycock,T.K.,eds.U.S.CensusBureau[USCB].2021a.MonthlypopulationestimatesforClimateScienceSpecialReport:FourthNationalClimateAssessment,theUnitedStates:April1,2010toDecember1,2020.https://www2.VolumeIWashington,DC:U.S.GlobalChangeResearchProgram.census.gov/programs-surveys/popest/tables/2010-2019/national/totals/207–230.https://doi.org/10.7930/J0H993CC.na-est2019-01.xlsx.(31August2021).FoodandAgricultureOrganizationoftheUnitedNations[FAO].U.S.CensusBureau[USCB].2021b.2017NationalPopulation2011.Thestateoftheworld’slandandwaterresourcesforfoodandProjectionsTables:AlternativeScenarios.https://www.census.gov/data/agriculture,summaryreport.Rome,Italy:FoodandAgriculturetables/2017/demo/popproj/2017-alternative-summary-tables.html.(31OrganizationoftheUnitedNations.47p.August2021).FoodandAgricultureOrganizationoftheUnitedNations[FAO].2020.U.S.CensusBureau[USCB].2021c.U.S.censusdata.https://www.Globalforestresourcesassessment2020:Mainreport.Rome,Italy.census.gov/programs-surveys/decennial-census/decade/2020/2020-https://doi.org/10.4060/ca9825en.census-main.html.(20August2021).Hayes,M.J.;Svoboda,M.D.;Wardlow,B.D.;Anderson,M.C.;Kogan,F.U.S.DepartmentofCommerce[USDC]BureauofEconomicAnalysis.2012.Droughtmonitoring:historicalandcurrentperspectives.Lincoln,2021.Domesticproductandincometable1.1.5.Grossdomesticproduct.NB:DroughtMitigationCenterFacultyPublications.94p.http://VersionAugust21,2021.digitalcommons.unl.edu/droughtfacpub/94.UnitedNations,DepartmentofEconomicandSocialAffairs,PopulationHeim,Jr.,R.R.2017.Acomparisonoftheearlytwenty-firstcenturyDivision.2019a.Worldpopulationprospects2019:highlights(ST/ESA/droughtintheUnitedStatestothe1930sand1950sdroughtepisodes.SER.A/423).BulletinoftheAmericanMeteorologicalSociety.98(12):2579–2592.https://doi.org/10.1175/BAMS-D-16-0080.1.UnitedNations,DepartmentofEconomicandSocialAffairs,PopulationDivision.2019b.Worldurbanizationprospects2018:highlights(ST/IntergovernmentalPanelonClimateChange[IPCC].2021.SummaryESA/SER.A/421).forpolicymakers.In:Masson-Delmotte,V.;Zhai,P.Pirani,A.;Connors,S.L.;Péan,C.;Berger,S.Caud,N;Chen,Y.;Goldfarb,L.;Gomis,M.I.;UnitedNations,DepartmentofEconomicandSocialAffairs,PopulationHuang,M.;Leitzell,K.;Lonnoy,E.;Matthews,J.B.R.;Maycock,T.K.;Division.2020.Worldsocialreport2020:inequalityinarapidlyWaterfield,T.Yelekçi,O.;Yu,R.;Zhou,B.eds.ClimateChange2021:changingworld.(ST/ESA/372).ThePhysicalScienceBasis.ContributionofWorkingGroupItotheSixthAssessmentReportoftheIntergovernmentalPanelonClimateUnitedNations,FrameworkConventiononClimateChange.2015.Change.CambridgeUniversityPress.InPress.AdoptionoftheParisAgreement,21stConferenceoftheParties,Paris:UnitedNations.InternationalLivestockResearchInstitute[ILRI],InternationalUnionforConservationofNature,FoodandAgricultureOrganizationofWorldBank.2016.Takingoninequality:povertyandsharedtheUnitedNations,WorldWideFundforNature,UNEnvironmentprosperity2016.https://openknowledge.worldbank.org/bitstream/Programme,andInternationalLandCoalition2021.Rangelandsatlas.handle/10986/25078/9781464809583.pdf?sequence=24&isAllowed=y.Nairobi,Kenya.(31August2021).InternationalMonetaryFund.2021.Worldeconomicoutlook:managingWorldBank.2021.WorldBanknationalaccountsdata,andOECDdivergentrecoveries.Washington,DC:April2021.NationalAccountsdatafiles.https://data.worldbank.org/indicator/NY.GDP.MKTP.KD.(20August2021).NOAANationalCentersforEnvironmentalInformation.2021a.Stateoftheclimate:globalclimatereportforannual2020.https://www.ncdc.noaa.gov/sotc/global/202013.(10September2021).2020ResourcesPlanningActAssessment2-7Chapter3FutureScenariosO’Dea,ClaireB.;Langner,LindaL.;Joyce,LindaA.;Prestemon,JeffreyP.;Wear,DavidN.2023.FutureScenarios.In:U.S.DepartmentofAgriculture,ForestService.2023.FutureofAmerica’sForestandRangelands:ForestService2020ResourcesPlanningActAssessment.Gen.Tech.Rep.WO-102.Washington,DC:3-1–3-13.Chapter3.https://doi.org/10.2737/WO-GTR-102-Chap3.TheResourcesPlanningAct(RPA)AssessmentusesBeginningwiththe2010RPAAssessment,asetofasetofscenariosofcoordinatedfutureclimate,integratedscenarioshasbeenusedtoframetheresourcepopulation,andsocioeconomicchangetoprojecttheanalyses.Thisapproachandanalyticalframeworkavailabilityandconditionofrenewableresourcesovertheweredesignedtobetterincorporategloballinkagesnext50years.Sinceitsinceptionin1974,RPAAssessmentsandinteractionsbetweennaturalresources,extendourhavealwayslooked5decadesintothefuture,butapproachesanalyticalcapabilitytoevaluatethepotentialeffectsofhavevaried.Beforethe2010RPA,futuresgenerallywereclimatechange,andmoreclearlythedescribecomplexityconstructedbasedonconsensusviewsonkeysocioeconomicanduncertaintyassociatedwithprojectingfuturevariablesaffectingdemandsforgoodsandservicesfromconditionsandtrends(USDAForestService2012).forestsandrangelands,resultinginonelikelyfuture.WecontinuethisapproachtodevelopscenariosfortheVariationsonthatfuturewereexploredbutlimitedinscope2020RPAAssessment.Thesescenariosdepictcoherent(e.g.,lowandhighpopulationgrowth),andwereofteninterdependentfuturesforglobalandU.S.populationfocusedonvariablesspecifictoforestproductmarkets(e.g.,dynamics,socioeconomicfactors,andclimatechange.lowandhighhousingstartsandalternativeassumptionsTheyalsoprovidequalitativeandquantitativeinputstotheaboutsoftwoodimportsfromCanada).GivenrapidRPAdomesticresourceanalyses,whichprojectresourceglobalizationinrecentdecades,theselimitedsocioeconomicconditionsandtrendsto2070.Thescenariosusedinthe“futures”becameinsufficienttoaddresstheforcesdriving2020RPAAssessmentaredescribedinthischapter.naturalresourcechangenationally.KeyFindings❖TheRPAAssessmentanalyzesthepotentialeffectsofglobalandnationaltrendsonallU.S.forestandrangelandsoverthenext50years.❖Acarefullyselectedsetofscenarios,definingandintegratingplausiblefutureclimate,population,andeconomicconditions,areusedtoorganizeprojectionwork.❖Allresourceareas(e.g.,forests,water,recreation,andwildlife)usethesamesetofscenariosorasubset(e.g.,climateonly)todefineaplausiblerangeofnaturalresourceavailabilityandconditionovera50-yearperiod,establishingaconsistentandcoordinatedapproach.❖ThedownscaledprojectionsofsocioeconomicandclimaticchangedevelopedfromthescenarioscanbeusedalongsideRPAresourceprojectionstoinformplanning,strategicthinking,andpolicydeliberationaboutthefuturefornaturalresourcemanagementandpolicyneeds.2020ResourcesPlanningActAssessment3-1FramingtheRPAAssessmentusedtoderivesocioeconomicandclimateprojections,whichScenariosrefertomodel-derivedestimatesofthefuture.ScenariosareusedtoexplorealternativefuturesandareAlthoughwereviewedandconsideredglobalscenariosintendedtoprovideaframeworkforobjectivelyevaluatingaconstructedbyotherresearchgroups(seeKoketal.2015plausiblerangeoffutureresourceoutcomes.Thisapproachforanevaluationofglobalscenarios),weselectedtheisparticularlyusefulwhenthereisconsiderableuncertaintycombinationoftheIPCC-basedclimateandsocioeconomicaboutthetrajectoriesofthedrivingforcesbehindpolitical,scenariosasthebasisforthe2020RPAAssessmentforeconomic,social,andecologicalchanges(Alcamoetal.severalreasons.Thesescenariosprovidequantitative2003,IPCC2007).AgloballylinkedscenarioapproachisdataonbothclimateandsocioeconomicvariablesoverimportantfortheRPAAssessmentbecauseglobalconditionsourassessmenttimehorizon,arewelldocumentedintheandtrendsinthesevariablesincreasinglyaffectdomesticscientificliterature,havebeenwidelyusedacrossalargenaturalresources.Well-definedglobalscenariosprovidearangeofimpactstudies,andweremorecurrentatthetimeofcoherentframeworkforevaluatingoutcomesacrossresourceselectionthanotheroptions.analyses.ConsistencyintheirconstructionallowsmanagersandpolicymakersadeeperunderstandingoftheconnectionsThe2020RPAAssessmentreliesontheapproachusedinandinteractionsamongthesevariablesaswellasinsightintotheIPCCFifthAssessmentReport(AR5)(IPCC2014)topotentialoptionsforenhancedadaptationormitigation.provideglobalcontextandquantitativelinkagesbetweenU.S.andglobaltrends.UnlikethesequentialapproachforAscenarioapproachcanusebothqualitativeandquantitativescenariodevelopmentusedintheIPCCThirdandFourthmethodstovisualizealternativefuturesbasedondifferentAssessmentReports,AR5usedaparallelprocess(Mossetsocioeconomicorinstitutionalassumptions.Theuseoftheal.2010):fourscenariosrepresentingalternativeclimateterm“scenario”canbeconfusingbecausescenariosarefutures(RepresentativeConcentrationPathwaysorRCPs)usedforvariouspurposes,orinreferencetospecifictypesweredevelopedindependentlyoffivesocioeconomicofscenarios(seeMossetal.2008,USGCRP2010).Forthescenarios(SharedSocioeconomicPathwaysorSSPs)RPAAssessment,wehaveadoptedtheapproachusedbythe(Nakićenovićetal.2014,O’Neilletal.2014).TherangeIntergovernmentalPanelonClimateChange(IPCC).TheofscenariosconsideredintheIPCCAR5providedabroadscenariosrepresentplausiblefuturestobetterunderstandspectrumofpotentialfutures.WeintegratedRCPandSSPhowsystemsmayrespondtodifferentratesofchangeorscenariostoensurethatthedegreeofatmosphericwarminghowdifferentdecisionsmayalterresourcetrajectories(MossindicatedbytheRCPisconsistentwiththeemissionsetal.2008).Scenariosarenotassignedlikelihoods,noraregeneratedbythesocioeconomicactivitydepictedintheSSPanyscenariosintendedtobe“accurate”perse.Rather,thesestoryline,andthattheintegratedscenariosdonotindicateconstructedscenariosprovideameansofqualitativelyandlargedeparturesfromcurrentnaturalresourcepolicies.quantitativelyunderstandinghowarangeofsocioeconomicandclimateconditionscouldinteractthroughtimetocreateTheremainderofthischapterdescribestheprocessuseddifferentnaturalresourcefutures.ScenariosareultimatelytoselectandintegratetwoglobalclimateandfourglobalsocioeconomicscenariosfromAR5intofourRPAscenariosTable3-1.Characteristicsofthefour2020RPAAssessmentscenarios.aCharacteristicScenarioLMScenarioHLScenarioHMScenarioHHGlobalwarmingandU.S.socioeconomicgrowthLowerwarmingandmoderateHighwarmingandlowHighwarmingandmoderateHighwarmingandhighGlobalrealGDPbgrowth,U.S.growthU.S.growthU.S.growthU.S.growth2020–2070MediumLowMediumHighGlobalpopulationgrowth,(4.9X)(3.2X)(4.6X)(6.9X)2020–2070LowcHighMediumLowU.S.realGDPgrowth,(1.2X)(1.6X)(1.4X)(1.2X)2020–2070MediumLowMediumHighU.S.populationgrowth,(3.0X)(1.9X)(2.8X)(4.7X)2020–2070MediumLowMediumHighGlobalemissions(1.5X)(1.0X)(1.4X)(1.9X)GlobalscenariolinksLowerHighHighHighRCP4.5-SSP1RCP8.5-SSP3RCP8.5-SSP2RCP8.5-SSP5aNumbersinparenthesesarethefactorsofchangeintheprojectionperiod.Forexamples,U.S.realgrossdomesticproductincreasesbyafactorof3.0between2020and2070inScenarioLM.bGDP=grossdomesticproduct(basedonestimatesbytheInternationalInstituteofAppliedSystemsAnalysis2019).cNote:Lowpopulationinvolvesinitialincreasewithdeclinesinthelatterdecadesoftheprojectionperiod.Source:Langneretal.2020.3-2FutureofAmerica’sForestsandRangelandsFigure3-1.Characterizationofthe2020RPAAssessmentscenariosintermsGlobalClimateScenariosoffuturechangesinatmosphericwarmingandU.S.socioeconomicgrowth.ThesecharacteristicsareassociatedwiththefourunderlyingRepresentativeFortheIPCCAR5,RepresentativeConcentrationPathwaysConcentrationPathway(RCP)–SharedSocioeconomicPathway(SSP)(RCPs)basedonradiativeforcingrepresentglobalclimatecombinations.scenarios(Mossetal.2010,USGCRP2017).Radiativeforcingisachangeinenergyfluxoftheatmosphere(warmingSource:Langneretal.2020.orcooling)overtime.Between1750and2019,naturalandanthropogenicfactorshaveincreasedradiativeforcingby(table3-1,figure3-1),andthendownscaleassociatedglobal2.72Watts/squaremeter(Wm-2),causingtheatmospheretoclimateandsocioeconomicprojectionstoafine-scalewarmduringthisperiod(IPCC2021).RCPsweredesignedtoresolutionacrosstheUnitedStates.Scenario“shortnames”explorepossibleclimatefuturesoverawiderangeofemissionaredefinedbasedontheclimatescenario’sglobalradiativelevelsandtheconsequencesoffutureincreasesinradiativeforcinglevels(firstletter)andthesocioeconomicscenario’sforcingby2100.ComponentsofradiativeforcingusedasU.S.growthcharacteristics(secondletter),asdescribedininputsforclimatemodelingincludeemissionsofgreenhousethefirstlineoftable3-1.Theterm“socioeconomicgrowth”gases,airpollutants,andlanduse(vanVuurenetal.2011).ismainlyfocusedontherateofpositivegrowthinaggregateAlargeradiativeforceimpliesalargerchangeintheclimate.economicoutputandinaggregatedisposablepersonalincomeFourRCPsweredefinedbydifferentlevelsoffutureradiativeintheUnitedStates.Therateofpopulationgrowthdiffersforcing:averylowforcinglevel(RCP2.6,or2.6Wm-2);twofromtherateofeconomicgrowthineachscenario,althoughmediumstabilizationscenarios(RCP4.5andRCP6.0);andthetwoalignintheirgeneraltrajectories.SimilartotheU.S.onehighforcinglevel(RCP8.5)(IPCC2014).NationalClimateAssessment(USGCRP2017)welabeltheRCP4.5climatescenarioas“lowerwarming”andtheForthe2020RPAAssessment,wechosetofollowtheRCP8.5climatescenarioas“highwarming.”ThefourRPAFourthNationalClimateAssessmentapproachforframingscenariosare:lowerwarming-moderateU.S.growth(LM),impactsofclimatechangebyusingRCP4.5andRCP8.5highwarming-lowU.S.growth(HL),highwarming-moderateasthetwoboundingclimatepathwaysforRPAprojectionsU.S.growth(HM),andhighwarming-highU.S.growth(HH).(JoyceandCoulson2020,Langneretal.2020).FromaTheselectedscenariossetthesocioeconomicandbiophysicalscientificviewpoint,exploringallavailablealternativefuturesboundsforevaluatingresourcefuturesinthe2020RPAisdesirable.Butresourceandtimeconstraints,aswellasAssessment.AmoreextensivedescriptionofRPAscenariocommunicationchallenges,requiredanarrowingofchoicesdevelopmentisavailableinLangneretal.(2020).fortheRPAAssessment.RCP2.6wasnotincludedintheRPAAssessmentanalysesbecauseextensivemitigationpolicyisClimateScenariosforthe2020requiredtoachievethislowerradiativeforcinglevel,andtheRPAAssessmentRPAAssessmentfocusesonfutureswithnosignificantchangefromcurrentpolicy.WealsodidnotconsiderRCP6.0becauseInthissectionwedescribetheprocessusedtoselectglobalresourceeffectsfromthatscenarioarelikelytofallbetweenclimatescenariosandamanageablesetofclimateprojectionsRCP4.5-andRCP8.5-basedanalyses.Usingbothalower-forthe2020RPAAssessment.Moredetailscanbefoundinendandahigherendscenario,RCPs4.5and8.5respectively,JoyceandCoulson(2020)andLangneretal.(2020).providesawiderangeoflong-termoutcomes.NationalClimateProjectionsResourceandtimeconstraintsalsoaffectedthenumberofclimatemodelsandprojectionsselected.ClimatemodelinginstitutionsacrosstheworldhaveusedtheRCPdatatoundertakecoordinatedexperimentswithdifferentglobalclimatemodels.Asaresult,thereare20ormoreclimateprojectionsperRCPavailableaspartoftheCoupledModelIntercomparisonProject,Phase5(CMIP5)(https://esgf-node.llnl.gov/projects/cmip5/)(Hayhoeetal.2017,KnuttiandSedlack2013).Tochooseasetofclimatemodelsandassociateddownscaledprojectionsforthe2020RPAAssessment,wefirstidentifiedtheclimatevariablesneededfortheresourceanalysesandthendevelopedcriteriaforselectingtheclimatemodelsandtheprojections(JoyceandCoulson2020,Langneretal.2020).2020ResourcesPlanningActAssessment3-3Basedontheresourceanalysisneedsofthe2020RPAprojectionwasselectedthatwasclosetothemeanchangeinAssessment,thedownscaleddatasetselectedwasMACAv2-temperatureandprecipitationofallmodelprojections.WeMETDATA(Abatzoglou2013,AbatzoglouandBrownwereabletoselectthesamemodelsforbothRCP4.5and2012).ThisdatasetcontainedstatisticallydownscaledRCP8.5forallvariables.projectionsfrom20differentglobalclimatemodels,eachrununderRCP4.5andRCP8.5.ThespatialresolutionforthisThissetoffivemodelsprovidesareasonableapproximationdownscaleddatasetwas4km(2.5miles),meetingthefine-oftheoverallprojectedtemperatureandprecipitationspacescaleneedsforRPAAssessmentresourceanalyses.Becauseencompassedbythelargersetof20models,butagreatlytheRPAAssessmentfocusesonthenext50years(throughreducedtotaleffort,therebymakingthesubsequentanalysis2070),weselectedmodelsthatprovidedtemperatureandfeasible(table3-2).Monthlydownscaledprojectionsforprecipitationforthisentireperiod,definingchangeasthetheconterminousUnitedStateswereobtainedandarchiveddifferencebetweenthefutureperiod(2041to2070)andtheintheU.S.DepartmentofAgriculture,ForestService’shistoricalperiod(1971to2000).ResearchDataArchive,alongwiththehistoricalclimateobservationsthatwereusedintheMACAdownscalingThreecriteriawereusedtoscreenindividualclimatemodelsprocess(CoulsonandJoyce2020,Joyceetal.2018);(JoyceandCoulson2020).Thefirstcriterionwashistoricaldownscaleddailyprojectionsareavailableonrequest.modelperformancetoeliminatefromfurtherconsiderationthosemodelsconsistentlyratedaspoorperformers(RuppAlthoughbeyondthescopeofthe2020RPAAssessment,2014,2016,Ruppetal.2013).ThesecondcriterionwasJoyceandCoulson(2020)alsoevaluatedtheutilityofthatonlyonemodelfromamodelinginstitutionwastheRPAclimatemodelselectionsforbehavioratendofselectedtoreducetheinfluenceofmodelinginstitutiononcentury(2070to2099)andforregionsoftheNationaltheprojections.ThethirdcriterionwastochoosethesameForestSystem(NFS).SeethesidebarUsingScenariosmodelforRCP4.5andRCP8.5,ifpossible,toreducemodelandProjectionsinResourceManagementPlanningforavariabilityacrosstheRCPs.descriptionofhowplannersmightthinkaboutusingclimateprojections.SeeJoyceandCoulson(2020)formoredetailedWeselectedfiveclimatemodelsthatcapturethefullrangeinformationabouttheselectionandutilityofRPAclimateoftemperatureandprecipitationprojectionsacrosstheentiremodelselections.setofmodels.Ensemblesthataverageprojectionsacrossmodels,therebyreducingvariability,haveoftenbeenusedSocioeconomicScenariosforthetoreducethenumberofprojections.Wechosenottouse2020RPAAssessmentanensemble,becausetheindividualmodelvariabilitymaybeimportantwhentheseprojectionsareusedasinputsinInthissectionwedescribetheprocessusedtoselectglobalresourcemodelingeffortssuchasforwater,forestcondition,socioeconomicpathwaysandcreatenationallydownscaledrangelands,andwildlife.Weidentifiedfourprojectionssocioeconomicdataforthe2020RPAAssessment.MorethatrepresentedtheleastchangeandthegreatestchangeindetailsonscenarioselectioncanbefoundinLangneretal.temperature(leastwarm,hottest)andthelargestdecrease(2020),andmoreinformationonthedownscalingprocessandgreatestincreaseinprecipitation(driest,wettest)forthecanbefoundinWearandPrestemon(2019a).conterminousUnitedStates.Althoughthesemodelseachrepresentthemagnitudeofchangeforoneclimatevariable,GlobalSocioeconomicScenariosknowledgeofwhateachmodelprojectsfortheotherclimatevariable(JoyceandCoulson2020)isimportantforproperSharedSocioeconomicPathways(SSPs)weredevelopedapplicationoftheinformation:modelsselectedtorepresentinparalleltotheRCPstoprovidescenariosofplausiblethemagnitudeofchangeforoneclimatevariable(suchsocietaldevelopmentinsupportoftheIPCCassessmentastemperature)maynotprojectthemid-rangevalueforprocess(O’Neilletal.2014).Theyconsistofdistincttheotherclimatevariable(suchasprecipitation).AfifthstorylinesthatcaptureuncertaintyaboutthefutureacrossTable3-2.ClimatemodelprojectionsselectedtoreflectdifferentU.S.climatefuturesintheyear2070.ClimatemodelLeastwarmHotDryWetMiddleInstitutionIPSL-CM5A-MRNorESM1-MMRI-CGCM3HadGEM2-ESCNRM-CM5InstitutPierreSimonNorwegianClimateMeteorologicalMetOfficeHadleyLaplace,FranceNationalCentreofCenter,NorwayResearchCentre,UnitedMeteorologicalResearch,KingdomInstitute,JapanFranceSource:JoyceandCoulson2020.3-4FutureofAmerica’sForestsandRangelandsUsingScenariosandProjectionsinResourceManagementPlanningClimatechangewillcontinuetoaffectthenaturalconditionstothealternativeoutcomesdepictedbytheRPAresourcesandecosystemservicesthataremanagedbyscenariosandclimateprojections.ManychangesoccurFederal,State,andprivatelandowners.Managershaveassystemsencounterthresholdsandtransitionfromonealongexperiencewiththeirlocalweather,climate,statetoanother,sometimeswithextremeconsequencesandresourceconditions;thechallengeisanticipatingandneedsforrapid,evenlarge-scaleinterventions.howfutureclimatechangewillaffecttheresources.UnderstandingandnavigatingthesetransitionscancreateJustashistoricalobservationscangiveapictureofpastadditionalopportunitiesformitigationandadaptation.climate,monthlyandannualclimateprojectionscanofferaplausiblefutureclimate,basedonassumptionsPlannersandmanagersmightalsoaskwhichandhowaboutatmosphericwarmingrelatedtoemissions,landmanyplausiblefuturestoexamine.Anoverwhelmingusechange,andourunderstandingoftheEarthsystem.numberofclimateprojectionsareavailable,andeachWorkingwithasetofplausiblefutureclimateprojectionsprojectionoffersinsightintothefuture.Theensemblecanfacilitateidentifyingfuturerisks,bothintermsof(oraverageofmanyprojections)isoftenusedtocapturefutureclimateoutcomesaswellasthetransitionsthatleadthetrend;however,individualmodelvariabilitymaybetothoseoutcomes.importantinmanagingriskstoresources.RPAprojectionswereselectedwiththeobjectiveofidentifyingafeasibleLandmanagersandplannersmightfirstaskhowfarinsetofprojectionsthatdescribetherangeoffuturethefutureisinformationneeded—5years,50years,or80climates—hot,leastwarm,dry,wet,andmiddle—toyears?Forexample,becausetreescanlivelongerthan50representtheboundsofthemostlikelyclimateoutcomeyearsandinfrastructureplanningoftenextendsbeyondbasedonourcurrentknowledge.Examiningthisrangethenextdecade,examiningthemoredistantfutureclimateoffuturescanallowplannersandmanagerstoassessmightbeimportant.ModelselectionfortheRPAscenariospotentialfuturevulnerabilitiesandpossibleworst-casewasbasedonbehaviorthrough2070butouranalysisscenarios.Resourcemanagerscanalsocomparetheirpastconcludedthatthesamecoremodelscouldbeusedtoexperienceswithaplausiblefuture.Forexample,ifthecapturetherangeofclimatefuturesforanend-of-centuryrecentclimatehasbeenhot,exploringthe“hot”projectionanalysis(2070to2099).Managersanddecisionmakersallowsexaminationoftheadditionalstressthatcouldbemightalsoconsiderpossibletransitionsfromtoday’splacedontheresourceinthefuture.Figure3-2.Relativecomparisonsofchangebymid-century(2041to2070)fromthehistoricalperiod(1971to2000)betweenRPAclimatemodelprojectionsacrossNationalForestSystemregionsfor(a)temperatureand(b)precipitationunder(left)RCP4.5and(right)RCP8.5.FiguresshowthatinallNFSregions:(a)thehotRPAprojection(HadGEM2-ES)isalwayshotterthantheleastwarmprojection(MRI-CGCM3)and(b)thewetRPAprojection(CNRM-CM5)isalwayswetterthanthedryprojection(IPSL-CM5A-MR).a)b)RCP4.5RCP8.5RCP4.5RCP8.5RCP=RepresentativeConcentrationPathway.2020ResourcesPlanningActAssessment3-5RPAprojectionswereselectedbasedonresultsfortheandmanagerstotheanalysisinJoyceandCoulson(2020)conterminousUnitedStates,butplannersmightinsteadtoexploretherelativerankingofclimatemodelsatthebefocusedonamorespecificspatialextent,suchasaregionalscale,butencourageuseoftheRPAclimatemodelNationalForestSystem(NFS)region(JoyceandCoulsonselectionswhenpossibleasthisalsoenablesuseofthe2020).DotheRPAprojectionsrepresentthesameclimateassociatedRPAresourceprojections.futuresattheregionalscale?RegionalclimatesvarygreatlyacrosstheUnitedStates—forexample,thedryTheseclimateprojections,alongsidesocioeconomicSouthwestandthewetPacificNorthwest.AttheNFSprojectionsandfuturelanduseprojections,areusedinregionalscale,therelativecomparisonsareappropriatetheRPAAssessmentchapterstoprojectplausiblefutureforallregions:thehotRPAprojectionisalwayshotterconditionandavailabilityofrenewableresources.Inthantheleastwarmprojectionandthewetprojectionadditiontotemperatureandprecipitationchange,otherisalwayswetterthanthedryRPAprojectionineachclimatevariablesarepartoftheclimatedataset(suchregion(figure3-2).Consequently,projectionsusedinthisaspotentialevapotranspiration)andhavebeenusedinreporthavecomparativevalueforNFSregions;however,projectingtheinfluenceoffuturedroughtonresourcealternativeprojectionsmightbepreferableforindividualavailability.InadditiontousingclimateprojectionsNFSregions.JoyceandCoulson(2020)analyzedall20directlyasdescribedhere,managersandplannerscanMACAv2-METDATAclimatemodelsbyNFSregiontoexaminethesocioeconomicprojectionsdescribeddeterminewhetheradifferentmodelmightproducebetterlaterinthischapter,aswellastheassociatedresourceabsoluteresultsforagivenNFSregion.Insomesituations,projectionsthroughouttheRPAAssessmenttoassesstheadifferentclimatemodelwasabetterrepresentativeofplausiblerangeofvulnerabilitiesandpossibleworst-casetherangewithintheregion.Forexample,whiletheRPAscenariosinfutureresourceavailabilityandcondition.Thewetmodelprojectswetterconditionsthanthedrymodelprojectionsprovidedthroughoutthe2020RPAAssessmentinallNFSregions,thedrymodelprojectswetconditionsarebaseduponthesamecorescenariosandrelyontheforNFSRegion6(PacificNorthwest)whileotherclimatesamefiveclimatemodels—allselectedtoencompassthemodelsprojectaverydryfuture(figure3-3).Therelativerangeofplausiblesocioeconomicandclimaticfutures.comparisonsbetweenthewetanddryprojectionsareResourceprojectionscanthereforealsobeinterpretedandappropriateforNFSRegion6,butplannersandmanagersimplementedasdescribedabove(e.g.,examiningfutureforthisregionmaywanttoexamineadifferentprojectionresourceconditionandavailabilityspecificallyassociatedtospecificallyplanforadryfuture.Wedirectplannerswithlowerorhighatmosphericwarming,differentlevelsoffuturesocioeconomicgrowth,anddifferentclimatefutures).Figure3-3.ProjectedchangesforNFSRegion6(PacificNorthwest)inannualprecipitation(percent)atmid-century(2041to2070)fromthehistoricalperiod(1971to2000)underRCP8.5.WhiletheRPAdrymodel(IPSL-CM5A-MR)projectsadrierfuturethantheRPAwetmodel(CNRM-CM5),thedrymodeldoesprojectanincreaseinprecipitationatmid-century,andtherearemanymodelswhichprojectadecreaseinannualprecipitationinthisregion.ModelnamesinboldarethenationalcoreRPAmodelsformid-century:leastwarm—MRI-CGCM3;hot—HadGEM2-ES;dry—IPSL-CM5A-MR;wet—CNRM-CM5;middle—NORESM1-M.3-6FutureofAmerica’sForestsandRangelandsseveralvariables:population,economicgrowth,technology,NationalSocioeconomicProjectionstrade,andgovernance.FiveSSPsweredeveloped,witheachdescribedintermsofthechallenges,costs,researchConsiderableeffortbytheclimatesciencecommunityanddevelopmentinvestments,anddegreeofpolicychangesdevotedtodownscalingclimateprojectionseliminatedtheinvolvedinmitigatingoradaptingtoclimatechange.FourneedtodevelopourowndownscaledclimatedatafortheoftheSSPsdescribetherangeofhighchallenges(difficult,2020RPAAssessment.Nosimilarefforthadbeendevotedtocostly,andentailinglargepolicyshifts)andlowchallengessocioeconomicscenarios—specificallytojointlydownscalingforglobaladaptationandmitigation,whileafifthSSPtheSSP-basedpopulationandeconomicprojections.definesanintermediatecase.AlthoughtheSSPscaptureProjectionsofpopulationandincomethataredownscaledarangeoffuturelevelsofsocioeconomicgrowth,noSSPusingaconsistentapproacharecriticalinputstovariousenvisionsafuturethatentailssustainednegativegrowth.RPAmodelingsystemsbecausetheyplayacentralroleinTheSSPsdonotincludeclimatefeedbacksorspecificpolicydeterminingnaturalresourcedemandsandimpactsacrossoptions(O’Neilletal.2014).theUnitedStates;wethereforedevelopedamethodologytodownscalethecountry-levelSSPdatatoafinerspatialThreedifferentmodelinggroupsdevelopedcountry-levelscale(Langneretal.2020,WearandPrestemon2019a).ThisprojectionsofbothpopulationandincomeconsistentwithapproachwasbasedoneconomictheoryandisconsistentSSPglobalnarratives.Forthe2020RPAAssessment,withcounty-scalehistoricalpatternsofchange(WearandwereliedontheeconomicprojectionsprovidedbythePrestemon2019a).AlthoughtheseprojectionscapturerecentInternationalInstituteforAppliedSystemsAnalysishistoricaltrendsinclimate,theydonotexplicitlyaccountfor(Cuaresma2017,IIASA2018)becauseIIASAincludedchangingclimatevariableswhenprojectingto2070,resultingmorecountry-levelprojectionsthatareimportantforinconsiderableuncertainty,particularlyinthelatteryearsmodelinginternationaltradeflowsasappliedinRPAoftheprojections.Risingsealevels,extendeddroughts,andmodelingofglobalwoodproductsmarkets.TodevelopextremeheatcouldpotentiallyalternotjustthemagnitudenationalsocioeconomicprojectionslinkedtotheglobalSSPsbutalsothedirectionofhistoricaltrends,whichisnotforuseintheRPAAssessment,wefocusedonSSPvariationincorporatedintoexistingprojections.Wehopetoexamineindemographicandeconomiccharacteristics,whichhavethepossibleimplicationsofdirectionalchangesinhistoricalbeenquantifiedatthecountrylevel(dataavailableonthetrendsthroughfutureresearch.SSPpublicdatabaseathttps://tntcat.iiasa.ac.at/SspDb/dsd?Action=htmlpage&page=welcome).Weappliedthemethodologytoestimatecounty-levelprojectionsforallfiveSSPs(WearandPrestemon2019a).GlobalandU.S.trendsdonotnecessarilyfollowthesameIntheseprojections,therateofpersonalincomechangetrajectoryacrossSSPs:globalpopulationtrendsandU.S.nationwide(summedacrossallcounties)wasconstrainedpopulationtrendsdiverge,whileU.S.trendsinGDPgrowthtomatchtherateofGDPchangenationwideasprojectedaremoreconsistentwithglobaltrends(Langneretal.2020).byIIASA(2018)fortheUnitedStatesforeachoftheSSPs.ThesepatternsaretiedtoseveralinteractingassumptionsUnderSSP3,populationgrowsslowlytoapeakin2035abouteconomicgrowth,fertilityandmortality,migrationandthengraduallydeclinesto2010populationlevelsbypatterns,andtheopennessoftheglobaleconomy.Aswith2070,whileincomegrowssteadilyatabout1percentperourclimatepathwayandprojectionselections,resourceandyear(fromabout$13billionin2010toabout$24billionintimeconstraintslimitedthenumberofSSPsselected.After2070).UnderSSP5,populationexpandsby86percent,fromperformingthedownscalinganalysisdescribedinthenext313millionto581millionbetween2010and2070,whilesection,weselectedfourofthefiveSSPstocapturetherealGDPgrowsatarateof2.5percentperyearbetweenmagnitudeofchangeinsocioeconomicconditionsacrossthe2010and2070,morethanquadruplingoverthisperiod.entireset(Langneretal.2020).WechoseSSP3andSSP5SSPs1,2,and4provideintermediateprojectionswithbecausetheyboundthedemographicandeconomicchangepopulationgrowingtobetween390millionand451million(lowandhighchange,respectively)fortheUnitedStatespeoplein2070andannualGDPgrowthratesofbetween1.4andcapturemostoftherangeinglobalchangeaswell.SSP1and1.8percent.andSSP2followsimilartrajectoriesfortheUnitedStatesandglobally;however,theunderlyingnarrativefortheseIntermsofpopulation,weprojectashiftintheNation’spathwaysoffersopportunitiestoexploredifferencesamongpopulationawayfromtheNortheastandMidwestandresource-andsector-specificvariablesthatcouldhavetowardtheSouthandWest,althoughtheratesofsuchdifferentimplicationsfornaturalresources.Forexample,interregionalpopulationshiftsvaryacrossSSPs;thethenarrativeforSSP1isfocusedonlow-emissionenergysmallestshiftsoccurunderthelowestpopulationgrowthsources,whereasSSP2ismoretightlylinkedtohistoricalrate.Projectionsindicatethatalargeshareofthecurrentpatternsofenergyuse.Therefore,wedecidedtoretainbothruralUnitedStateswillexperienceeitherneworcontinuedSSP1andSSP2.WeeliminatedSSP4becauseitstrajectorypopulationlossesorstablepopulationacrossallscenariosfallsbetweenSSP3andSSP2.whileurbanareasexpand(seeWearandPrestemon2020ResourcesPlanningActAssessment3-72019afordetails).Asdescribedabove,onlydownscaledtheseSSPswithRCP8.5-basedclimateprojections,oursocioeconomicprojectionsforSSPs1,2,3,and5wereusedresultscouldoverstateclimateinfluence.tosupportresourceprojectionsinthe2020RPAAssessment.Theobservedcounty-levelpopulationandpersonalincomeWeacknowledgethatmanypairingsmightbeplausibledatafrom2010andprojectionsoverthe2015to2070(assessingthemutualconsistencyoftheirassumptionsisperiodusedinthe2020RPAAssessmentarearchivedintheinexact);however,weselectedfourRCP-SSPcombinationsUSDAForestService’sResearchDataArchive(Wearandtounderpin2020RPAAssessmentanalysesofresourcePrestemon2019b).effectswithoutsignificantpolicychanges(table3-1,figure3-1).Thefour2020RPAAssessmentscenarios2020RPAScenariosencompassmostoftheprojectedrangeofclimatechangefromtheRCPsandprojectedquantitativeandqualitativeRPAscenarioswereconstructedbylinkingtheRCPsrangeofsocioeconomicchangefromtheSSPs,resulting(climatefutures)withSSPs(socioeconomicfutures).TheinfourdistinctfuturesthatvaryacrossamultitudeofRCPsandSSPsweredevelopedtoprovideascenariocharacteristics(figure3-4).TherangeofchangesinglobalmatrixarchitecturetoassistinthedevelopmentofcommonandU.S.characteristicsissimilarbetweenthe2010andscenariosthatcanbeusedacrossdifferentclimatechange2020RPAAssessmentscenarios.FortheUnitedStates,researchcommunities.WhiletheRPAAssessmentscenarioseconomicandpopulationgrowthtrendsinitiallymoveinneedtolinktothegeneralworldviewsoftheRCPandSSPthesamedirectionacrossscenarios(withpopulationgrowthfutures,theyalsomustprovideacompellingrangeoffuturesturningtoshrinkageunderSSP3fortheUnitedStatesafterfortheUnitedStatesandbeavailableatthefinespatialscale2040),whereasglobally,economicandpopulationgrowthneededtomatchtheeconomicandecologicalcontextofthedivergeinthreeofthefourscenarios.ThesequantitativeRPAresourceanalyses.trendsandnarrativesprovideaunifyingframeworkthatorganizestheRPAAssessmentnaturalresourcesectorAsdescribedabove,RCPs4.5and8.5wereselectedasanalysesaroundaconsistentsetofpossibleworldviews.lowandhighboundingpathwaystocapturetherangeofplausiblewarmingfutures,andSSPs1,2,3,and5wereLinking2020RPAAssessmentScenariosselectedtocapturetherangeofsocioeconomicchange;toNaturalResourceSectorsthisresultedineightpossibleRCP-SSPcombinationsforthe2020RPAAssessmentscenarios.WhenpairedwithDefiningthe2020RPAAssessmentscenariosisthebeginningthefiveclimateprojections,wewerefacing40potentialoftheRPAanalysisprocess.TheRPAscientiststhenfuturesocioeconomic-climateoutcomesfortheUniteddeterminehowtousethescenariodataandassumptionsinStates—exceedingtheanalyticalcapacityoftheAssessment.theirresourcesectoranalyses.EachanalysisusesdifferentHowever,notallpotentialRCP-SSPcombinationscouldcombinationsofthescenariovariablesandresource-specificbeplausiblylinked(Riahietal.2017).TolinkanRCPandvariablestoevaluatefutureresourceoutcomes.ExamplesSSPintoanintegratedscenario,thedegreeofatmosphericofconnectionsbetweencomponentsofthe2020RPAwarmingindicatedbytheRCPmustbeconsistentwiththeAssessmentscenariosandRPAAssessmentresourceanalysesemissionsgeneratedbythesocioeconomicactivitydepicted(figure3-5)illustratethenumerousroutesthroughwhichtheintheSSPstoryline.BecausetheRPAAssessmentanalysesscenariovariablescaninfluenceresourceanalyses.Insomearebasedoncontinuationofcurrentpolicies,weselectedcases,bothsocioeconomicandclimateprojectionsaredirectRCP-SSPcombinationsthatdidnotrequireassumptionsthatinputstoresourceanalyses,includingoutdoorrecreationwouldindicatelargedeparturesfromcurrentpoliciesforthedemand,watervulnerability,andforestproductsupplyandRPAAssessmentscenarios(Langneretal.2020).demand.Inothercases,onlytheclimatevariablesaredirectinputstotheanalyses,forexample,inprojectionsofrangelandWepairedRCPsandSSPsusingthefollowinglogic.SSP1productivityandstressonterrestrialhabitats.istheonlybaselinescenariothatresultedinradiativeforcingclosetotheRCP4.5levelandwasjudgedtoLanduseandlandscapepatternprojectionsareoftenthebetheonlySSPthatcouldplausiblylinkwithRCP4.5intermediarybetweenthescenariosandresource-specificforRPAAssessmentpurposes.Combininganyoftheeffects(figure3-5).ThelanduseprojectionsincorporateremainingSSPswithRCP4.5wouldrequirevaryinglevelstheU.S.climateandsocioeconomicprojections.Inturn,oftechnologyorpolicyassumptionsthatarebeyondthethelandscapepatternprojectionsarebasedonthelandusescopeofRPAAssessmentanalysesexceptwhentheRPAprojections(Brooksetal.2020).Landuseprojectionsareframeworkisusedspecificallyforpolicyanalysis.SSP5canstronglyinfluencedbypopulationandeconomicdrivers;beplausiblylinkedwithRCP8.5forAssessmentpurposes.changesaremorerapidandmoreextensiveinfuturesofTheremainingSSPs—SSP2andSSP3—producedforcinghigherpopulationsormorerapideconomicgrowth(orlevelsbetweenRCP6.0andRCP8.5.Becausewepairedboth).Analysesthatrelyonlyonthelanduseorlandscape3-8FutureofAmerica’sForestsandRangelandsFigure3-4.Characteristicsdifferentiatingthe2020RPAAssessmentscenarios.ThesecharacteristicsareassociatedwiththefourunderlyingRepresentativeConcentrationPathway(RCP)–SharedSocioeconomicPathway(SSP)combinations.Figure3-5.PathwayforincorporationofglobalscenariosintoRPAresourceanalyses.GlobalscenarioprojectionsaredownscaledacrosstheU.S.andeitherincorporateddirectlyintoRPAresourceanalysisorindirectly(throughlanduse/landscapepatternprojections).RPAresourceanalysesareexamplesandnotintendedtobeanexhaustivelist.2020RPAScenariosExamplesofRPAResourceAnalysesGlobalScenariosU.S.ProjectionsForestDynamics4SharedCounty-levelLandUseRangelandProductivitySocioeconomicIncomePathways/SSPLandscapeWaterVulnerabilityCounty-levelPatternAt-riskSpeciesDatabasePopulationForestFragmentation2RepresentativeU.S.ClimateVariableForestProductSupplyandDemandConcentration(4km)(MACAv.2)OutdoorRecreationDemandPathways/CMIP5StressonTerrastrialHabitatsSource:Langneretal.2020.2020ResourcesPlanningActAssessment3-9patternsincorporatethescenariovariablesindirectly,insteadatangiblepictureoftheplausiblefutureoftheseresourcesofdirectlymodelingtheeffectsofclimate,population,etc.absentintervention.MoreinformationaboutthelanduseandlandscapepatternprojectionsareavailableintheLandResourcesChapter.ConclusionsAdditionally,someresourcesfactorindividualscenarioTheRPAscenariosandtheirunderlyingassumptionsstorylinesintotheirmodel-basedassumptions.Inthecaseprovideacommonandcoherentframeworkfordevelopingofforestproducts,forexample,inadditiontothedirectprojectionsofnaturalresourceimpactsintheRPAincorporationofscenariovariables,theFOrestResourceAssessment.BuiltfromtheIPCCglobalRepresentativeOutlookModel(FOROM)ofglobaltradealsoincorporatesConcentrationPathwaysandSharedSocioeconomicdifferencesacrossscenariosintradeopenness,technologyPathways,thesenational,downscaledscenariosaddresschangerates,productionandconsumptionincreasesinthelegislativemandateforRPAresourceprojections.wood-basedbioenergy,andforestgrowthratechangesBecausetheRPAscenariosandclimatemodelsweregloballyanddomestically(Johnstonetal.2021).selectedtocapturetherangeofplausiblefutureclimateandsocioeconomicvariability,thefutureofglobalanddomesticLangneretal.(2020)providesabroadoverviewofthenaturalresourcescandiffersubstantiallyacrossthefourfour2020RPAAssessmentscenarios,focusingonhowscenariosand20scenario-climatefutures.Projectingthetheclimateandsocioeconomicprojectionsandqualitativerangeofplausiblefuturesforournaturalresourcesallowsaspectsofeachscenariomayaffectnaturalresourceforabetterunderstandingofhowtheunderlyingclimateandconditionsandtrends.TheindividualRPAAssessmentsocioeconomicdriversofchangecanalternaturalresourceresourcechaptersprovidequantitativemodelingresultsandconditionsandcreatechallengesacrosstheUnitedStates.COVID-19ImplicationsonRPAScenariosTheSARS-CoV2virusandassociatedCOVID-19illnessnightlyreservationsin2020,andvisitationtoundevelopedwerefirstidentifiedattheendof2019,andtheWorldHealthgeneralforestsettingsrisingbymorethan50percentOrganizationdeclaredaglobalCOVID-19pandemiconMarchwhencomparedwith2015(seetheOutdoorRecreation11,2020.TheCOVID-19diseaseresultedinwidespreadpublicChapter).Globalsupplychains—alreadystressedbeforehealthandeconomy-wideimpacts.Governmentsaroundthethepandemicduetotradetensions,particularlybetweentheworldimplementedstrictlockdownregulationstocontainUnitedStatesandChina—haveseensignificantdisruptionsthespreadofthevirus,which,alongwithfearsofcontractinganddelaysduetothecollapseandsubsequentincreaseintheCOVID-19illness,shrankeconomicactivitytolowsconsumerdemand,leadingtohigherconsumerpricesfornotexperiencedindecadesandglobalemissionstolevelsmanycommoditiesandatleasttemporaryinflation.TheU.S.notexperiencedsincetheearly2000s.Whiletheeconomiclabormarkethasalsoexperienceddisruptions,beginningcontractionwasworsethanthe2007to2009financialcrisiswithsignificantunemploymentduringlockdown(definedbyandassociateddeeprecession,growthreturnedmorequicklystay-at-homeordersandmassquarantines)andfollowedbyduetofiscalsupportinafewlargeeconomiesandthearrivallaborshortagesincertainindustries.TheU.S.forestproductsofvaccines(InternationalMonetaryFund2021).TheU.S.sectorexperiencedsupplyanddemanddynamicstoextentsrecessionwastheshortestonrecord,at2months,andU.S.realnothistoricallyregistered,behaviorsalllinkedtoCOVID-19GDPexceededitspre-COVIDlevelbythesecondquarterofdirectly(illness-relatedmillstaffingshortages)orindirectly2021(USDCBureauofEconomicAnalysis2021).Emissions(seeForestProductsChapter).alsoreboundedrapidlyalongsideeconomicactivity;globalemissionsinDecember2020were2percenthigherthaninMorethan2yearsintothepandemic,itisnotknowniforDecember2019(IEA2021).howthesedisruptionswillinfluencelong-termtrends.Forexample,theeffectsonFederallandsvisitationfromotherOtherCOVID-19relateddisruptionsappeartobelongersignificanteventsinrecentdecades(e.g.,theSeptemberlasting.U.S.metropolitanareashaveseendenseurban11,2001,terroristattacks,the2007to2009GreatFinancialcorepopulationsshiftintotheoutersuburbs,primarilyanCrisis,andspikesingasolineprices)havebeentransitory.accelerationofpre-pandemictrendsandlikelyduetotheAlternatively,NaturalResourcesInstituteFinland(UNECEproliferationofremotework(Patinoetal.2021).Visitationto2021,Viitanenetal.2020)predictspermanenteffectsonpubliclandsincreasedsignificantlyduringthepandemic,withforestproductsmarkets,forexamplethedemandfortissuecampgroundsseeinganearly40-percentincreaseinaverageandhygienepaperproductsaswellassomepackaging3-10FutureofAmerica’sForestsandRangelandsmaterialsispredictedtopermanentlyshiftupward,duetoanandclimatefutures,incorporatinglow-andhigh-warmingincreaseddemandforproductsthatsupportgreaterhygienefuturesalongsideawidevarietyofsocioeconomicfuturesandincreasede-commerce,respectively.andclimatemodelsthatcovertheboundariesofexistingclimateprojections.ThesescenarioswouldonlybeTheRPAscenariosweredevelopedbeforethearrivalofirrelevantifeffectsofCOVID-19permanentlyforcetheU.S.theglobalpandemicandassociatedglobalrecession.Thesocioeconomicorclimatefuturesbeyondtheseboundaries;RPAscenariodevelopmentandassociateddownscalingearlydataandpatternsfromthepastyearsuggestthatthisprocessdescribedinthischapterisamulti-yearprocess,andisunlikely.Thepandemicismorelikelytochangethedownscaledprojectionsarenecessaryinputstosubsequentmagnitudeofimportantmodelparametersthantochangetheresourcemodelingefforts.Apotentialconcernisthatthedirectionoftheireffects,meaningthatwearemorelikelytoscenario-basedmodelingofalternativefuturesemployedseetemporarychangestoorpermanentintensificationsofintheRPAAssessmentwouldhavebeendifferenthadtheexistingtrendsthanwholescaleupheavalsoflongstandingfullimplicationsofCOVID-19beenknown.Weassertthatpatternsandrelationships.thecurrentlyunderstoodimplicationsofCOVID-19wouldnotalterourRPAscenariodevelopmenttoanyconsiderableAsthepandemicprogressesandhopefullyends,datawilldegree.Asdescribedinthischapter,theRPAscenarioscontinuetobecollectedaboutconsequencesofCOVID-19originatewithglobalscenariosproducedbytheIPCC.ThethatcouldhaveimplicationsforrenewableresourcesinIPCChasnotreleasedrevisedglobalscenariosbecauseoftheUnitedStates.Wewillcontinuetomonitornewdatathepandemic.AnychangestotheRPAscenarioswouldandhopetoassesspotentiallong-termimpactsinournextthereforebedisconnectedfromglobalprojectionsandAssessment.Earlydataisanalyzedforseveralresourcesinassumptions,resultinginobstaclesandinconsistenciesinthisAssessment—seeCOVID-19sidebarsintheDisturbanceourgloballylinkedanalyses(forexample,ouranalysesofChapter,theForestProductsChapter,andtheOutdoorforestproductmarkets).Inaddition,theRPAscenarioswereRecreationChapterforanalysesoftheeffectsofearlystagesselectedtoencompasstherangeofplausiblesocioeconomicofthepandemicontheseresources.LiteratureCitedDokken,D.J.;Stewart,B.C.;Maycock,T.K.,eds.Climatesciencespecialreport:FourthNationalClimateAssessment,VolumeI.Washington,DC:Abatzoglou,J.T.2013.DevelopmentofgriddedsurfacemeteorologicalU.S.GlobalChangeResearchProgram.33–160.dataforecologicalapplicationsandmodelling.InternationalJournalofClimatology.33(1):121–131.https://doi.org/10.1002/joc.3413.IntergovernmentalPanelonClimateChange(IPCC).2001.Climatechange2001:synthesisreport.AcontributionofWorkingGroupsI,II,Abatzoglou,J.T.;Brown,T.J.201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sment.Gen.Tech.Rep.WO-102.Washington,DC:4-1–4-37.Chapter4.https://doi.org/10.2737/WO-GTR-102-Chap4.ThelandresourcesoftheUnitedStateshaveaffectlandscapepatternsincludingforestfragmentation.Weexperiencedsignificantchangessincethe2010thensummarizelanduseprojectionsunderfuturescenariosResourcesPlanningAct(RPA)Assessment,andcontinualandevaluateprojectedchangesinimperviousandtreecoverschangeisexpectedinmostlandscapesbecauseofbothandlandscapepatterns.Geographicregionsreportedinthisnaturalandhumanactions.ThischaptersummarizesrecentchaptergenerallyfollowtheRPAregions(asshowninfiguretrendsoflanduseandlandcoveracrosstheconterminous2-1intheIntroductionChapter),exceptthattheStatesofUnitedStatesandpresentsfutureprojectionsto2070basedAlaskaandHawaiiarenotincluded.LaterchaptersprovideonRPAscenarios.Webeginbyhighlightingthekeyfindingsmoreinformationabouttheconditionandhealthofforests,fromasupportingRPAanalysisofhistoricalchangesintherangeland,andotherspecificlandresources.landbaseandevaluatinghowrecentlandcoverchangesKeyFindings❖Developedlandscontinuetoencroachonnaturalecosystemsandagriculturalareas,withabouthalfofnewdevelopedlandsconvertingfromforestorrangeland.❖Developedlandsareprojectedtocontinuetoexpandinallscenarios,althoughlessthanprojectedinthe2010RPAAssessment.Theexpansionofdevelopedlandsvariesacrossregionsandisprojectedtobelargerunderhighsocioeconomicgrowthscenariosandsmallerunderhotterclimatefutures.❖Forestlandareaincreasedslightlyoverthepastdecades,mostlyattheexpenseofpastureandcroplandareas.Thistrendisexpectedtoshifttodecreasingforestareaunderallscenarios,althoughatlowerratesthanprojectedbythe2010Assessment.❖Forestcoverfragmentationslowedoverthepastdecadebutcontinuesoverallandisexpectedtocontinueintothefutureforthewesternandsoutheasternsubregions,whiledecreasingslightlyinthenorthandcentralsubregions.❖ChangesinunfragmentedforestlandcoveraremoredynamicinprivateforestsoftheSouth,whilechangesintheWestareslowerandconcentratedinpubliclands.❖Mostforestlandsremainin“natural”landscapes,butanincreasingproportionisexpectedtobein“interface”landscapesneardevelopedoragricultureuseinthefuture.❖Economicandregionalfactorstendtobemoreimportantdriversoflanduseareachangesthanchangesinclimaticconditions.2020ResourcesPlanningActAssessment4-1HistoricalLandUsecategory.NetchangereferstothedifferencebetweentheandLandCoverareainacategoryatdifferenttimes.Netpercentchangeiscalculatedastheratioofnetareachangetotheareaatthe❖AccordingtoNationalResourcesInventorydata,firsttime.developedlandshadthelargestnetincreaseofLandusereferstothesocialandeconomicintentforwhichalllandusesfrom1982to2012—withforestandlandisused,whilelandcoverreferstothevegetation,exposedagriculture(cropandpasture)landscontributinglandsurfaces,water,andartificialstructurescoveringthelandaboutequallytonewdevelopedland—whilecropsurfaceatagiventime(Coulstonetal.2014).Landuseclasseslandshadthelargestdecrease.Forestgainsfromoftenincorporatebothpastuseandintendedfutureuse,inotherlanduses(primarilyfromconvertedpasture)additiontocurrentconditions,whilelandcoverclassesrelateexceededforestlossestootherlanduses(mostlytoconditionsonlyataspecifictime(e.g.,theinstantatwhichtodeveloped),resultinginaslightnetincreaseinsatelliteimageryisacquired).Forexample,substantiallossofforestlandarea.treecanopy(e.g.,duetowildfire,wind,orharvest)resultsintemporarylossofforestcoverduringthesubsequentchanges❖Developedlandareaexpandedatanincreasingfrombaregroundtograssandshrub,butultimatelytheareaisagainclassifiedasforestcoverwhentreesattainsufficientratefrom1982to1997,thencontinuedtoexpandheightandcover.However,theforestlanduseofthatsameatadecreasingrateuntil2012.disturbedareadoesnotchangebecausenopermanentlandusechangeoccurred.Manyinconsistenciesbetweenland❖ChangesintheU.S.landbasedifferdependingclassificationsrelatetodifferencesinthetemporalframeworkofdefinitionsandobservations.Therefore,thechoiceofoneonwhetherlanduseorlandcoverisbeinglandclassificationsystemoveranotherdependsonthespecificexamined.After2000,changesinlanduseandresourcequestionbeingasked,thedataavailabletoaddresslandcoveracrosstheconterminousUnitedthequestion,andthetimeframeoftheanalysis.Stateswerebroadlysimilarforagricultureanddevelopedland,butlesssoforforestland.InthisreportweusetwocomplementaryUSDAinventoriesThedifferencesinforestchangebetweenland(FIAandNRI)torepresentcurrentandprojectedfuturelandusedataandlandcoverdataweremostlydueuseconditions.Theseinventoriesarebasedonstatisticaltotemporarylossesofforestcover(canopysamplesofplots,precludingtheiruseforspatiallyexplicitdisturbancessuchasharvestorwildfire)thatdidanalysessuchaslandscapepatternassessmentforwhichlandnotchangetheforestlanduse.coverdata(NLCD)arebettersuited.Eachofthefollowingsectionsrefersspecificallyto“landuse”or“landcover”Maintainingproductiveforestsandrangelandsrequiresdependinguponwhichdatawereused.Whileitissometimesmonitoringofthoseresourcesandanalysisofchangeinpossibletocompareestimatesoflandcoverandestimatesofrelationtosociety’schangingneedsandexpectationsaslanduse,suchcomparisonsoftenrevealonlythedefinitionalwellasachangingclimate(seethesidebarForestCarbonortemporaldifferencesbetweendatasources.Insomecases,LandBase).ChangesinU.S.forestsandrangelandsaffectbothtypesofdatahavebeenintegratedtoimprovethetheirassociatedresources,underscoringtheimportanceinterpretationofresults.ofmonitoringandexaminingtrendsinlanduseandlandcover.BecausetheRPAAssessmentisamulti-resourceNationalResourcesInventoryonassessmentwheresocial,economic,andbiologicalNon-FederalLanddimensionsareallimportant,bothlanduseandlandcoverperspectivesareconsidered.ThissectionsummarizesNRIestimatesoflandusestatusandtrendsarebasedonthekeyfindingsfromarecentRPAAssessmentofland5-yearreportsspanninga30-yearperiod(1982,1987,resourcesacrosstheconterminousUnitedStates(Nelson1992,1997,2002,2007,2012).The2017NRIReportwasetal.2020)anddescribesthedatausedforthefuturepublishedaftercompletionofRPAanalysesoflanduseprojectionsoflandresourceslaterinthischapter.TheRPAstatusandfutureprojections.ResultsforNRI2017arelandbaseanalysesusedatafromfourprimarysources:generallysimilarto2012butarenotincludedhere.ForesttheU.S.DepartmentofAgriculture,ForestServiceForestlandusecomprisedthelargestshareofnon-FederallandInventoryandAnalysisProgram(FIA)(landuseinBurrillin2012(411millionacres,26.8percent),followedcloselyetal.2018);theUSDANaturalResourcesConservationbyrangeland(405million,26.4percent)(Nelsonetal.ServiceNationalResourcesInventory(NRI)(non-Federal2020).Between1982and2012,therewerenetlossesoflanduseinUSDA2015);theNationalLandCovercrop,pasture,andrangelandarea,andnetgainsofforest,Database(NLCD)(landcoverinUSGS2019a,b,c,d);anddeveloped,andConservationReserveProgram(CRP)areatheU.S.CensusBureau(USCB)(humandemographicsinU.S.CensusBureau2017a,b).Ingeneral,grosschangeforagivencategoryoflanduseorcoverreferstoareatransitionsto(grossloss)orfrom(grossgain)another4-2FutureofAmerica’sForestsandRangelands(figure4-1).TherewasnoCRPareain1982becauseCRPgaininforestwastheapproximately20millionacresenrollmentsbeganin1986.Croplandhadthelargestareaconvertedfrompasture.Netlossinrangelandwascauseddecline(approximately57millionacres),whiledevelopedpredominatelybyconversionstocrop,developed,andlandhadthelargestincrease(approximately42millionpasturelands,butlosseswerepartiallyoffsetbyconversionsacres).Whileforestlandareahadonlyaslightincreasetorangelandfromcrop,pasture,andforestlands.Theseduringthisperiod,therewassignificantgrosschangecumulativechangesresultfromperiodicnetchangeswhich(i.e.,forestareaconvertedbothtoandfromotheruses).emphasizedifferenttypesoftransitionsovertimeattheThelargestlossofforestlandwastheapproximately18scaleofboththeconterminousUnitedStates(figure4-1)andmillionacresconvertedtodevelopedland,andthelargestRPAregions(figure4-2).Figure4-1.NRIareatrendsinlanduseclasses(bars)and5-yearnetchangeinlanduseclasses(lines)intheconterminousUnitedStatesfrom1982to2012.Source:USDA2015.(AdaptedfromFigure3inNelsonetal.2020.)Figure4-2.NRItrendsin5-yearnetareachangeinlanduseclassesfrom1987to2012byRPAregion.NorthSouthRockyMountainNetchange(millionacres)Netchange(millionacres)Netchange(millionacres)YearYearYearPacificCoastNoteaxischanges.Source:USDA2015.Netchange(millionacres)Year2020ResourcesPlanningActAssessment4-3ForestCarbonLandBaseTheforestlandbaseoftheUnitedStatesoffersmany(from1990untiltwoyearsbeforethepresent),facilitatingecosystemservices.Oneimportantserviceistheremovalproperaccounting.In2023,themostrecentestimatesofofcarbondioxide(CO2)fromtheatmosphere.AspartlandsectoremissionsandremovalswillbesubtractedoftheUnitedStates’commitmenttotheUnitedNationsfromtheestimatesinthebaseyear2005todeterminetheFrameworkConventiononClimateChange(UNFCCC),contributionofthelandsectorandthelandusecategoriesestimatesofemissionsandremovalsofCO2andotherwithinittotheU.S.NDC.Thismeansthatestimatesofthegreenhousegasesarereportedannually,notonlyforforestlandbaseandthecarbonstocksandchangesonthatforestbutacrossalllandusecategoriesandsectorsofthelandbaseareofcriticalimportance.economyintheNationalInventoryReport(NIR)(USEPA2020).ThelandusedefinitionsusedintheNIRfollowSince1990,theareaofforestremainingforesthasbeentheIntergovernmentalPanelonClimateChange(IPCC)relativelystableatapproximately692to693millionacres.guidelinesfornationalgreenhousegasinventories(seeLossesthatoccurredthroughthe1990sweregenerallyEggelstonetal.2006).Theselandusedefinitionsdifferoffsetbygainsinforestremainingforestfrom2005tofromthoseusedinthischapter.Thepurposeofthissidebar2016(figure4-3).In2017and2018,therewerelossesistodescriberecenttrendsintheforestlandbaseusedforinforestremainingforestofapproximately0.4and0.3UnitedStatescarbonreporting.millionacresrespectively(figure4-4).Thedominanttransitionsintoandoutofforestinvolvedthegrassland,UnitedStatesforests(includingAlaskaandHawaii)andcropland,andsettlementlanduses.Since1990,79milliontheharvestedwoodproductsobtainedfromthemoffsetacresofgrasslandand11millionacresofcroplandhavetheequivalentof11percentofCO2emissionsfromotherbeenconvertedtoforestland.Thesegainswereoffsetsectorseachyear(seetheForestResourcesChapterforduringthatperiodbyforestlossesof41millionacrestocarbonprojections).Forestinformationisreportedaspartgrassland,8millionacrestocropland,and35millionacresoftheLandUse,LandUseChange,andForestrychaptertosettlement.TheannualconversionrateofgrasslandoftheNIR,followingIPCCgood-practiceguidelines.toforesthassharplydeclinedsince2013fromapeakofTherearetwoimportantpracticesrelatedtothereportedabout3millionacresperyearto2.45millionacresperforestlanduseinformation:onlymanagedlandsareyear,whilereciprocalconversionremainedrelativelyconsidered(97percentofallforestlandisconsideredstableatabout1.5millionacresperyear(figure4-4).Themanaged;Ogleetal.2018),andlandconvertedtoforestrateofforestconversiontosettlementincreasedfromistrackedseparatelyfrom“forestremainingforest”for1990to2005andhasbeenrelativelystablesincethenataperiodof20yearsafterconversion(Eggelstonetal.approximately1.4millionacresperyear(figure4-4).2006).Afterthat20-yearperiod,theconvertedlandmaybeconsideredasforestremainingforest.AdheringtothoseTheamountofforestandtrendsinlanduseconversionpracticesresultsinestimatesoftheforestlandbasethathaveadirectimpactontheamountofCO2theforestsdifferfromotherestimatesinthisreport.oftheUnitedStatessequesterandstore(Domkeetal.2020a).Sincethe1990s,thelandusetrendsthatsupportTheinformationcontainedintheNIR,alongwiththeNIRhavechanged(USEPA2020).FutureshiftsinprojectionsofCO2emissionsandreductions,informthelandusewillinfluencetheCO2sequestrationandcarbonnationallydeterminedcontribution(NDC)fortheUnitedstoragecapacitythatforestlandcurrentlyprovides.TheStatesundertheParisAgreement.NDCsforeachcountryamountofforestareaaswellasdisturbancedynamics,articulateeffortstoreducenationalemissionsandadaptharvestingforfiber,andforestgrowthdefinesthetotheimpactsofclimatechange.TheUnitedStatessequestrationpotentialofU.S.forests(Domkeetal.accountsforemissionsreductionsinthelandsectorwith2020b).Understandingtherangeofpotentialfutureshifts2005asthebaseyear.Thedata,methods,andmodelsinlanduse,disturbance,harvest,andgrowthcaninformusedtoestimateemissionsandremovalsareappliedpolicydiscussiononemissionreductiontargets(CoulstonconsistentlyovertheentireUNFCCCreportingperiodetal.2015,WearandCoulston2019).4-4FutureofAmerica’sForestsandRangelandsFigure4-3.AreaofU.S.“forestremainingforest”from2005toFigure4-4.Keylandusetransitionsaffectingtheareaof“forest2018.remainingforest”2005to2018.Source:Domkeetal.2020a.Source:Domkeetal.2020a.CensusBureauUrbannon-Federallandin2011(416millionacres,27.6percent),AreaandPopulationfollowedbycropland(309million,20.5percent)(Nelsonetal.2020).Between2001and2011,therewerenetlossesMorethan80percentoftheU.S.populationlivedinurbanofcrop,pasture,andforestlands,andnetgainsofshrub,areasin2010,anincreasefrom75percentin1990(Nelsongrass,developed,andother(water,barren,herbaceousetal.2020).Census-definedurbanareaalsoexpandedduringwetland)lands.Consideringbothnon-FederalandFederalthattime,increasingfrom2.1percent(47millionacres)tolands,forestcomprisedthelargestshareoflandcoverin3.0percent(68millionacres)oftotallandarea,withlargertheRPANorthandSouthRegionsin2011,whileshrubwasincreasesoccurringwithinthemosturbanizedcounties.thedominantlandcoverintheRockyMountainandPacificStateswiththelargesturbanareain2010wereTexas(5.6CoastRegions(Nelsonetal.2020).Forestcoverchangemillionacres),California(5.3millionacres),andFloridafrom2001to2011wasdominatedbygainsandlosses(4.7millionacres).Stateswiththelargestpercentageoffromortograssandshrubcovers,forbothFederalandurbanlandin2010wereNewJersey(39.8percent),Rhodenon-FederalownershipswithinallfourRPAregions.MostIsland(38.7percent),andMassachusetts(38.0percent).ofthenetlandcoverchangesfrom2001to2011occurredThelargestareaofurbanlandgrowthfrom1990to2010innon-Federalownerships,whichcomprisedmorethanoccurredinTexas(1.9millionacres),Florida(1.8millionthree-fourthsofthetotalareaoftheconterminousUnitedacres),andGeorgia(1.4millionacres),whilethelargestStates.Developedlandhadthelargestpercentnetchange(anpercentagegrowthinurbanlandoccurredinNevada(128.6increase)inallRPAregions,almostallonnon-Federalland,percent),Delaware(91.4percent),andNorthCarolinawhilepatternsoflandcovertransitionsonFederallands(87.8percent).TheexpansionofurbanareahasdriventhevariedsubstantiallyamongRPAregions.expansionofthewildland-urbaninterface(seethesidebarWildland-UrbanInterface).ComparingLandUseandLandCoverTransitionsNationalLandCoverDatabaseAfter2000,changesinlanduseandlandcoveronnon-RPAanalysesofforestcoverincludetheNLCDwoodyFederallandintheconterminousUnitedStateswerebroadlywetlandsclassandthethreeNLCDuplandforestclasses.similarforbothagricultureanddevelopedland,butlesssoForgeneralcomparisonswiththenon-Federalstatisticsforforestland.Thedifferencesinforestchangebetweenlandcitedabove,forestlandcovercomprisedthelargestshareofusedata(NRI)andlandcoverdata(NLCD)weremostlydue2020ResourcesPlanningActAssessment4-5totemporarychangesinforestcover(canopydisturbances)andSouthRegions,resultinginaslightnetgaininforestthatdidnotchangetheforestlanduse.Becausethereislanduse(Nelsonetal.2020).FIAdatawereinsufficienttonorangelandclassinNLCD,theNLCDshrubandgrassestimatechangeintheRPARockyMountainandPacificclassesareoftenusedassurrogatesforrangeland.However,CoastRegions.AccordingtoNRIdata,non-FederallandsportionsoftheNLCDshrub,grass,andbarrencoverclassesexperiencedaverageannualratesofforestchangebetweenare(regenerating)forestlanduse,whileaportionofNLCD2002and2012of0.18percentfromforesttononforestandgrasscoverispasturelanduse.Thefactthatthosecoverand0.19percentfromnonforesttoforest,resultinginnegligibleuseclassespartiallyoverlappreventsdirectcomparisonsofnetchangeinnon-Federalforestlanduse.Thus,bothlandlandcoverareaandchangewithlanduseareaandchangeusedatasets(FIA,NRI)revealsimilartrendsinforestland(Nelsonetal.2020).ThesidebarProtectedForestAreaisusearea.Inageneralcomparison,forestlandcoverbetweenanexampleofananalysisthatisrelativelyinsensitiveto2001to2011experiencedaverageannualratesofforestdifferencesbetweenlanduseandlandcover.coverchangeacrossallownershipsof0.46percentfromforesttononforestand0.17percentfromnonforesttoforest,ThestatusandtrendsofFIAforestlandareawererecentlyresultinginanetlossofNLCDforestcover(Nelsonetal.updatedinasupportingRPAreport(Oswaltetal.2019).2020).FortheRPANorthandSouthRegions,theaverageComparisonsofFIAdatawithNRIandNLCDdataduringannualnetlossofforestcoverwas0.28percent.TheselandcommonperiodsshowedthattheaverageannualratesofcovertrendsinthetwoeasternRPAregionsdifferslightlyFIAforestlandusechangebetween2001and2011werefromlandusetrends,duemostlytodifferencesinhowforest0.26percentfromforesttononforestand0.34percentfromcanopydisturbancesareclassified(Nelsonetal.2020).nonforesttoforestforallownershipsacrosstheRPANorthWildland-UrbanInterfaceThewildland-urbaninterface(WUI),definedastheareaTrackingtheextentoftheWUIprovidesinsightsintowherehousesareinornearwildlandvegetation,combinesecologicalconditionsandmanagementconcernsinbothlanduse(residential)andlandcover(forest,grass,residentialareaswithwildlandvegetation(Zippereretal.shrub)toidentifyanenvironmentofuniqueinterestinpress).tonaturalresourcemanagers(Radeloffetal.2005).HousingdevelopmentinforestedandothernaturallyRadeloffetal.(2018)mappedWUIextentandchangevegetatedecosystemsisofparticularinterestbecausefrom1990to2010acrosstheconterminousUnitedStateshousingdevelopmentisincreasingfasterthanpopulationusingdecennialCensusdata(numberofhousingunits)(Bradburyetal.2014)andcanhavesignificantecologicalandlandcoverdata(wildlandvegetationcoverage)toeffects(Pejcharetal.2015).Whennativevegetationislostdeterminewherehousingisintermixedwith,oradjacenttoandfragmentedbyhousesandassociatedinfrastructure,wildlandvegetation.WUIenvironmentswerewidespreadnonnativespeciesareintroduced,pollutionincreases,in2010,coveringmorethan190millionacres(10percentzoonoticdiseasesaretransmitted,andwildfiresbecomeoftotalarea)andcontaining43.4millionhousingunitsmorecommon,challenging,andcostly(Hansenetal.(33percentofallhousingunits)(figure4-5).From19902005,Bar-Massadaetal.2014,Syphardetal.2017).to2010,theWUIareagrewby46.8millionacres(33Figure4-5.Totalarea(left)andnumberofhousingunits(right)inthewildland-urbaninterfaceoftheconterminousUnitedStatesin1990and2010.Source:Radeloffetal.2017.4-6FutureofAmerica’sForestsandRangelandspercent),anarealargerthanthatofWashingtonState,andcomparedtotheeasternregions,therelativelyhigherthenumberofhousingunitsintheWUIincreasedby41westerngrowthratesresultedfromrelativelysmallerpercent.In2010,theWUIcontained43percentofthe29.2absolutegains.millionnewhousingunitsbuiltbetween1990and2010.TherearestrikingregionaldifferencesinthepercentofForestlandcomprisesamajorshareoftheWUIarea.ThetotalareaandtotalnumberofhousingunitsintheWUIFIAforestlandin2013(USDAForestService2020)was(figure4-6)andgrowthrates(figure4-7).evaluatedintermsofitsWUIstatusinarecentassessmentofWUIresearchneeds(Mockrinetal.inpress).In1990,WUIextent,growth,andratesofincreaseareallofthatforestlandoccupiednearly70millionacres(49interesttolandmanagers.Extentandgrowthindicatepercent)ofthetotalWUIarea,andtheWUIcontainedtheneedfornaturalresourcemanagers,suchasthose10percentofthenation’sforestland.OverthenexttwoFigure4-6.PercentoftotalareaandpercentoftotalhousingunitsinFigure4-7.Percentgrowthinwildland-urbaninterfaceareaandthewildland-urbaninterfacein2010,byRPAregion.numberofhousingunitsfrom1990to2010,byRPAregion.Source:Radeloffetal.2017.Source:Radeloffetal.2017.whoworktoreducewildfirerisk,toengageinoutreachdecades,thepercentoftotalWUIareathatwasforesttonewWUIresidents,whilegrowthratesareakeylanddidnotchangemuch,butWUIexpansionincreasedconcerntomanagersofchangingforestandresidentialtheshareofthenation’stotalforestlandareafoundinenvironments.ThenumberofWUIhomesandtheamountWUIenvironments.By2010,forestlandoccupied90ofWUIareaareconsistentlylargerintheRPANorthandmillionacres(51percent)ofthetotalWUIareaandtheSouthRegions,whereforestedareashavealonghistoryWUIcontained14percentoftotalforestland.Acrossallofhousingdevelopment.Inthoseregions,theWUIisayears,approximately85percentoftheforestlandintherelativelylargerportionoftotalregionarea.TheSouthWUIwasinthe“lowhousingdensityintermix”WUIRegionisnotableforextensiveandprevalentWUIarea,class,whichrepresentstheleastdevelopedWUIareas.aswellasrelativelyhighratesofgrowth.InthewesternThemajority(80percent)oftheforestlandintheseWUIregions,smallerWUIareasexperiencedrapidgrowthareaswasprivately-owned,typicallyindividual-orfamily-from1990to2010,particularlyinthenumberofhousingownedforests,while16percentwasinprivatecorporateunits.TheRockyMountainRegionhadthesmallestWUIownership.In2010,justoverone-quarterofthenationalarea,butitcontained42percentofallhousingunitsintotalof306millionacresofindividual-orfamily-ownedthatregionandexperiencedthefastestgrowthofbothforestlandareawasintheWUI.WUIareaandhousingunitsfrom1990to2010.When2020ResourcesPlanningActAssessment4-7ProtectedForestAreaProtectedforestshelptoconservethenaturalfunctioningbeenassignedtoanIUCNcategory.Mostpubliclandsofforestswhilepreservingirreplaceablelandscapes(ErvinbothsatisfytheIUCNdefinitionoftheSustainableUse2003).TheProtectedAreasDatabaseoftheUnitedStatescategory(VI)andapproximatetheHabitatManagement(PAD-US;ConservationBiologyInstitute2016)mapstheareascategory(IV)forsomethreatssuchasinvasiveplantknownprotectedareas(heldinfee-simpleownership),occurrence(Riittersetal.2018),justifyinguseofthedealongwiththestatusofeachprotectedareaaccordingfactocategoryforpubliclandsnotcurrentlyassigned.toguidelinesdevelopedbytheInternationalUnionfortheConservationofNature(IUCN;DudleyandStoltonComprisingover30percentofthetotalforestarea(table2008).AccordingtoNelsonetal.(2020),95percentof4-1),publiclyownedandprotectedforestareamaybethetotalprotectedforestareaisheldineitherFederalortheNation’slargestplannedlanduse.Approximately14Stateownership,ofwhich38percentisintheRPARockypercentoftotalforestareaoccurredinadesignatedIUCNMountainRegion,29percentintheNorthRegion,17category,andanadditional18to20percenthaddefactopercentinthePacificCoastRegion,and16percentinprotection.WildernessareascontainedthelargestsharestheSouthRegion.Forthisreport,protectedforestareaofprotectedforestarea,whilethesmallestshareswereestimatesintheconterminousUnitedStateswereupdatedcontainedinnaturereserves,nationalparks,andnaturaltotheyear2016forforestcover(USGS2019d)andforestmonuments.Whiletheareaofprotectedforestdependsonlanduse(Burrilletal.2018).Inadditiontotheseventhedefinitionofforestaslandcover(NLCD)orlanduseIUCNprotectioncategories,adefactoprotectioncategory(FIA),thesharesoftotalforestareaineachofthesevenincludedFederal-andState-ownedareathathasnotyetIUCNprotectioncategoriesissimilarforbothcases.Table4-1.ProtectedforestcoverandforestlanduseareaintheconterminousUnitedStates,circa2016.ForestareaPercentoftotalIUCNprotectedforestareaItemNLCDforestFIAforestlandNLCDforestFIAforestlandcoverusecoveruseIUCNprotectioncategoryamillionacrespercentIaNaturereserve111.21.3IbWildernessarea253333.534.2IINationalpark788.88.4IIINaturalmonument121.62.5IVHabitatmanagement151618.116.6VProtectedlandscape141817.018.8VISustainableuse161719.718.2AllIUCNprotectioncategoriesDefactoprotectionb7996100100NoprotectioncTotalforestaread106140390449575685PercentwithIUCNprotection13.7%14.0%Percentwithdefactoprotection18.5%20.4%FIA=ForestInventoryandAnalysis.IUCN=InternationalUnionfortheConservationofNature.NLCD=NationalLandCoverDatabase.aIUCNprotectioncategorydefinitionssource:https://www.iucn.org/theme/protected-areas/about/protected-area-categories.bFederalandStateownershipnotyetassignedtoanIUCNcategory.cNotinFederalorStateownershipandnotyetassignedtoanIUCNcategory.dTotalsmaydifferslightlyfromelsewhereinthisreport.Entriesmaynotsumtocolumntotalsbecauseofrounding.ExcludesDistrictofColumbia.Sources:USGS2019d;Burrilletal.2018;ConservationBiologyInstitute2016.4-8FutureofAmerica’sForestsandRangelandsHistoricalForestFragmentationimproveinterpretationofthefindings,keyresultsfromtheandLandscapeContextanalysisareintegratedwithforestlanduseinformationfromtheForestInventoryandAnalysis(FIA)databasecirca2016,❖Drivenbya2.6percentnetlossofforestcoverandwithforestcanopydisturbanceinformation(Schleeweisetal.2020)from2000to2010.areafrom2001to2016,fragmentationincreasedinallRPAregionsoverawiderangeofspatialLandCoverChangescales.However,therateofforestcoverlossandfragmentationdecreasedafter2006inallregions.Overallchangesinlandcoverareaareanecessarybaselineforevaluatinglandscapepatternchangesovertime.Theprevious❖Inboth2001and2016,88percentofforestsectiondescribedthelandcoverareachangesfrom2001to2011thatwerereportedbyNelsonetal.(2020).Withthecoverareawasinlandscapesdominatedbyreleaseofthe2016NationalLandCoverDatabase(NLCD)“natural”landcovers(forest,grass,shrub,water,whichwasusedforthislandscapepatternanalysis,Homerwetland,orbarrencover),while31percentwasetal.(2020)providedadetailedanalysisoflandcoverareain“interface”landscapescontainingatleast10changesacrosstheconterminousUnitedStatesfrom2001topercentofdevelopedoragriculturelandcover.2016.TosupplementtheinformationinNelsonetal.(2020),abriefupdateoflandcoverareachangessetsabaselinefor❖From2001to2016,thelossofforestcoverarealandscapepatternchangesfrom2001to2016.washighestwithinlandscapesdominatedbyThelandscapepatternsdescribedinthissectiondependdevelopedlandcover(9percent),butthetotalprimarilyonthreegeneralizedcovertypes:forest(includingforestareaoccurringindeveloped-dominatedtheNLCDuplandforestandwoodywetlandclasses),landscapesincreasedby18percentasthoseagriculture(includingcropandpastureclasses),andlandscapesexpandedtoincludeadditionalforestdeveloped(whichincludesmostoftheimperviousroadarea.Thelossofforestcoverareawaslowestinsurfacesaswellasurbanclasses).From2001to2016,thereagriculture-dominatedlandscapes(1percent),werenetgainsofdevelopedcoverareaandnetlossesofforestbutthetotalforestareainagriculture-dominatedcoverareainallRPAregions,whiletheagriculturecoverarealandscapesdecreasedby5percentasthoseincreasedinthewesternregions(PacificCoastandRockylandscapescontractedtoexcludeadditionalforestMountain)anddecreasedintheeasternregions(Northandarea.South;table4-2).Unlikethetwowesternregions,forestlossesthatoccurredinthetwoeasternregionsintheearly2000s❖Mostofthegrosschanges(lossandgain)ofcorewerepartiallyoffsetbylatergains.Overallregions,the5-yearnetgainsindevelopedcoverandlossesinforestcoverbecame(unfragmented)forestcoveroccurredonprivatesmallerovertime,andagriculturelossesthatoccurredearlierlandintheRPASouthRegion,whilemostofthenetinthetimeframewerebalancedbylatergainssuchthatthelossoccurredonpubliclandinthePacificCoast15-yearnetchangewasrelativelysmall.andRockyMountainRegions.ForestCoverFragmentation❖Mostoftheforest-nonforestcoveredgeintheForestfragmentationwasassessedbymeasuringforestvicinityoffragmentedforestlandin2016wasareadensity(FAD),whichindicates“howmuchforestisassociatedwithshruborgrasslandintheRockysurroundedbyhowmuchotherforest,”andisspecificallyMountainandPacificCoastRegionsandwiththeproportionofaneighborhoodsurroundingagivenforestdevelopedoragriculturelandintheNorthandlocationthatalsohasforestcover(Riittersetal.2002).SouthRegions.TheinterpretationofFADisstraightforward:ifforestsarenotfragmentedthenFADequals1.0forallforestTheprecedingsectiondescribedthelandbaseintermsoflocationsandneighborhoodsizes,andFADdecreasesastheareaofindividualresourcecomponentssuchasforestfragmentationincreases.Fragmentationisthereforerelativeandagriculturelands.Anothercomponentofthelandbasetoacompletelyforestedcondition,anddeviationsfromthatisthelandscape,thatis,thetypeandspatialarrangementofbaselinearisefromnatural(andendemic)fragmentationastheresourcesthatarecontainedinagivenarea.Forexample,wellasanthropogenicfragmentation.RiittersandRobertsonaforestedlandscapecontainsmostlyforestlandarea,while(2021)summarizedresultsacrosstheconterminousUnitedaforest-developedinterfacelandscapecontainssubstantialStatesusingNLCDdatafor2001,2006,2011,and2016forestanddevelopedlandareas.Suchlandscapepatterns(USGS2019a,b,c,d),documentingincreasedfragmentationinfluencethelocationsandtypesofforestchangesthatoccur,aswellastheecologicaleffectsofthosechangesandthesocialvaluesplacedonthemindifferentcircumstances.Usinglandcovermapsfrom2001to2016,thissectionaddressesseveralaspectsofforestlandscapepatterns,includingforestfragmentationandtheanthropogeniccontextofforests.To2020ResourcesPlanningActAssessment4-9from2001to2016overawiderangeofneighborhoodsizes.interiorforestlossesexceeding5percentwerefrequentintheThisreporthighlightsthestatusandtrendsof“interior”PacificCoastandRockyMountainRegionsbutlesscommonforestcoverfora38-acreneighborhoodsize,whereaforestintheNorthandSouthRegions,wheremanycountieslocationisconsidered“interior”iftheFADvalueinitsexhibitednetgainsofinteriorforestarea.Largepercentageneighborhoodisatleast0.9(i.e.,iftheneighborhoodisatchangesofinteriorforestareawerecommoninrelativelyleast90percentforested;McIntyreandHobbs1999).Noteless-forestedcounties,buttherelativelysmallareaofforestthatthesamedefinitionofinteriorforestwasappliedtoforestinthosecountieshadlittleinfluenceonnationalstatistics.landuseprojectionsinthelatersectiononProjectedForestThenetlossof2.6percentoftotalforestareaacrosstheFragmentationandLandscapeContextbutwithadifferentconterminousUnitedStates(table4-2)translatedtoanoverallneighborhoodsize.netlossof6.4percentofinteriorforestarea,butnetlossratesvariedfrom3to13percentamongRPAregions(table4-3).ThenetchangeofinteriorforestareadoesnotnecessarilyMostofthenetchangestointeriorforestareaoccurredbeforeequalthenetchangeoftotalforestareabecauseinteriorforest2006,afterwhichtherateofnetlossdecreasedinallregions,changeoccursattheneighborhoodscaleandtotalforestareawithindicationsofstabilizationornetgainsafter2006inthechangeoccursatthepixelscale(RiittersandWickham2012).twoeasternregions.Theinteriorstatusofagivenlocationcanchange“directly”whenthatlocationitselfchanges,or“indirectly”whenTheindicationsofstabilizationorrecoveryofinteriorforestneighboringlocationschange.Thus,directchangereferstoareadonotimplytherewerenoimportantchangesduringthegainorlossofforestatthatlocation,whileindirectchangethelatertimeperiods—onlythatthegrossgainsoffsetgrossresultsfromforestgainsorlossesintheneighborhoodoflosses.Thatdoesnotaccountfordifferencesinthelocationspersistentforest.ofinteriorforestovertime,whichcaninfluencetheregionalsustainabilityofinterior-dependentecologicalprocesses.ItisthereforeusefultoexaminebothformsofforestchangeatIntheRPASouthRegion,forexample,theoverallnetlossalargergeographicscale,suchasonaper-countybasis(figureofinteriorforestareafrom2001to2016(3millionacres;4-8).Therewasanetlossofinteriorforestareain2,054oftable4-3)resultedfromgrosschanges(directandindirect)3,109countiesfrom2001to2016.Ofthose,1,042countiesinvolving42.1millionacres(table4-4).Thegrossgainofexhibitedlossesofmorethan5percentand334countieshad19.7millionacresofinteriorforest(directandindirect)lossesofmorethan15percent.Inforest-dominatedcounties,Table4-2.Totalandperiodicnetareachangeinagriculture,developed,andforestlandcoverfrom2001to2016,byRPAregion.Statisticsfor2001to2011maydifferfromtheRPALandBasereport(Nelsonetal.2020)becausethepreviouseditionsofNLCDlandcovermapswereupdatedwiththereleaseofthe2016edition.RPAregionLandcoverAreain20162001to2006Netchange2011to2016Totalnetchangemillionacresmillionacres2006to2011millionacres2001to2016ConterminousU.S.AgriculturemillionacrespercentDeveloped450-2.43.30.3North1063.40.31.57.2Forest575-12.02.2-0.2-2.6SouthAgriculture171-0.8-3.2-0.2-1.0Developed380.9-0.70.35.2RockyMountain185-2.20.60.1-1.1Forest128-2.5--a0.5-2.2PacificCoastAgriculture421.7-0.90.89.7Developed215-4.51.11.8-1.2NLCD=NationalLandCoverDatabase.1281.00.12.84.6aValuebetween-0.05and0.05.Forest150.51.90.37.4Sources:USGS2019a,b,c,d.Agriculture111-2.90.3-1.7-5.7Developed22-0.1-2.20.20.4110.2--0.14.6Forest63-2.50.1-0.5-6.2Agriculture-1.2DevelopedForest4-10FutureofAmerica’sForestsandRangelandsFigure4-8.Per-countynetpercentchangein(a)totalforestcoverareaand(b)interiorforestcoverarea(38-acreneighborhoodsize)from2001to2016.(a)(b)Source:USGS2019a,d.intheSouthRegionduringthistimeperiodimpliesthatusingasmallerneighborhood(11acres)andahigherFADapproximatelyone-fifthofthatregion’sinteriorforestareathreshold(100percent)toobtainabetterrepresentationofin2016wasinadifferentlocationcomparedto2001.ThefragmentationintheimmediatevicinityofFIAforestplots.indirectchangeswererelativelylargerthandirectchanges,particularlyintheNorthandSouthRegions,butlesssoinIn2001,266.7millionacres(40percent)oftheFIA2016thePacificCoastandRockyMountainRegions,suggestingforestareawasclassifiedascoreforest.Thelossandthatthespatialpatternsofoverallforestareachangetendedgainofcoreforeststatus(41.5and26.3millionacres,tobemoredispersedintheeasternregionsandmorerespectively)reducedtheareaofcoreforestto251.5millionconcentratedinthewesternregions.acresin2016.In2016,morethanone-halfofallcoreareaintheconterminousUnitedStateswasprivatelyownedTointegrateforestcoverandforestusedatawhenevaluating(140.9millionacres),andtwo-thirdsofthatareawasinfragmentation,measurementsofFAD(forestcover)werenoncorporateprivateownership(90.9millionacres).PubliccombinedwithFIAfieldplotdata(forestuseinBurrilletownershipaccountedfor110.6millionacresofcorearea,al.2018,Oswaltetal.2019).ThisanalysisusedasetofwiththeFederalgovernmentowningthree-fourthsofthatplotsrepresenting96percent(659.3millionacres)ofallarea(81.3millionacres).ConsistentwiththeregionalFIAforestland(includingwoodland)in2016;exoticanddifferencesinprivateversuspublicforestlandownershipraretypesofforestwereexcluded.Eachplotlocationwas(Oswaltetal.2019),mostofthewesterncoreareawasattributedwithits“core”foreststatus(yesorno)in2001publiclyownedwhilemostoftheeasterncoreareawasand2016,wherecoreforestwasdefinedasalocationwithprivatelyowned(figure4-9).MostofthetotalgrossgainandFAD=1.0(i.e.,theneighborhoodis100percentforested)grosslossofcoreareaoccurredonprivatelyownedlandininthesurrounding11-acreneighborhood.AsinprevioustheSouthRegion(table4-5).InboththeNorthandSouthRPAreports(e.g.,USDAForestService2016),thisRegions,thelossesonprivatelyownedlandsubstantiallyproceduredifferedfromtheanalysisof“interior”forestbyexceededthegains.Incontrast,two-thirdsofthetotalnetTable4-3.Totalandperiodicnetchangeininteriorforestcoverarea(38-acreneighborhoodsize)from2001to2016,byRPAregion.InteriorforestareaNetchangeTotalnetchange2006to2011RPAregion200120162001to2006millionacres2011to20162001to2016millionacresmillionacresConterminousU.S.millionacresmillionacres-3.3millionacrespercentNorth295276-15.0--a-0.6-19-6.4South9793-3.70.5-0.2-4-4.0RockyMountain10097-5.0-2.51.9-3-2.7PacificCoast6254-3.3-1.3-1.8-8-12.33732-2.9-0.5-5-12.8aValuebetween-0.05and0.05.Sources:USGS2019a,b,c,d.2020ResourcesPlanningActAssessment4-11Table4-4.Componentsofinteriorforestcoverarea(38-acreneighborhood)changefrom2001to2016,byRPAregion.InteriorforestlossInteriorforestgainRPAregionDirectaIndirectbDirectcIndirectdmillionacresmillionacresmillionacresmillionacresConterminousU.S.21.127.410.718.9North3.06.91.54.4South9.213.27.712.0RockyMountain5.03.70.30.9PacificCoast3.93.51.11.6aAunitofinteriorforestwaslostbyconversionofthatunitfromforesttononforestcover.bAunitofinteriorforestwaslostduetoforestcoverlossintheneighborhoodofapersistentforestunit.cAunitofinteriorforestwasgainedbyconversionofthatunitfromnonforesttoforest.dAunitofinteriorforestwasgainedduetoforestcovergainintheneighborhoodofapersistentforestunit.Sources:USGS2019a,d.changeofcoreareaoccurredintheRockyMountainandthat87percentofcorearealossintheconterminousUnitedPacificCoastRegions,typicallyonpubliclyownedlands.AsStateswasassociatedwithnearbycanopyremoval,whilearesult,theconterminousUnitedStatestotalnetchangeofdisturbancesbyfireorstressoccurrednear21percentofthecoreareawasroughlythesameforpublicandprivatelands.coreforestloss.(Notethatmultipledisturbancescouldhaveoccurredneareachplot.)NearbydisturbancebyfireorstressTobetterunderstandtheproximatedriversofcoreareawasnotcommonintheeasternforesttypegroups(figureloss,forestdisturbance(canopyloss)attributiondatafrom4-10);whilefireorstressmayoccurrelativelyfrequentlyin2001to2010(Schleeweisetal.2020)wasintegratedwithsomeofthoseeasternforesttypes,theyaregenerallylocalizedthelandcoverandFIAdata.EachFIAplotlocationthatoroflowenoughseveritynottoremovetheforestcanopy,changedfromcoretonon-corestatusbetween2001andandthereforelargelynotappearintheeasterntypegroups.2011wasattributedwithoneormoretypesofdisturbanceAmongwesternforesttypegroups,nearbydisturbanceby(removal,fire,and/orstress;seetheDisturbancestoForestsfirewasrelativelycommoninallforesttypegroupsexceptandRangelandsChapter)thatoccurredinthesurroundingthreethataretypicaloftemperaterainforest(hemlock/Sitka11-acreneighborhood.Disturbancesintheneighborhoodofspruce,redwood,alder/maple),andnearbydisturbancebyfireFIAplotsthatchangedfromcoretonon-corestatusindicatedFigure4-9.TheareaofFIAforestlanduseintheconterminousUnitedStateswithcoreforestcoverstatus(11-acreneighborhoodsize)in2001and2016,byRPAregionandownershipcategory.Thecirclesindicatethepercentageofforestareathatwascorein2016.Sources:USGS(2019a,d);Burrilletal.(2018).4-12FutureofAmerica’sForestsandRangelandsTable4-5.Grossandnetchangeofcoreforestcoverstatus(11-acrewasmorecommonthandisturbancebyremovalinfourforestneighborhood)for2016FIAforestland,byRPAregionandownership.Publictypegroupswheretimberharvestingislesscommon(pinyon/ownershipincludesFederalandStateandlocal.Privateownershipincludesjuniper,westernoak,tanoak/laurel,woodlandhardwoods)corporateandnoncorporate.alongwithoneforesttypegroupthatexperiencedextensivewildfires(lodgepolepine).NearbystresswascommoninonlyRPAregionOwnershipLossGainNetchange10ofthe28foresttypegroups,mostlyintheWest.BecausemillionacresmillionacresmillionacrescoreareatendstooccurinrelativelyremoteareaswherefireConterminousPublicandstressaremorecommon,theassociationofcoreareaU.S.Private12.55.0-7.4losswiththosedisturbancetypeswasoftenhigherthanthe29.021.3-7.7overallexposureofallforestareatothosedisturbancetypesNorthPublic2.32.0-0.3(seetheDisturbancestoForestsandRangelandsChapter).ForPrivate6.73.8-2.9example,approximately5percentofallpinyon/juniperforest1.51.60.1areawasexposedtonearbystressfromfire,butoverhalftheSouthPublic18.116.1-2.0lossofcoreareawasassociatedwithnearbyfire.Private5.50.6-4.81.30.2-1.2AnanalysistosupportinterpretationofthepotentialimpactsRockyPublic3.10.8-2.3associatedwithfragmentationconsideredalarger38-acreMountainPrivate2.91.2-1.6neighborhoodandattributedeachFIAplotlocationwiththefrequenciesofthetypesofforest-nonforest“edges”inthatPacificCoastPublicneighborhood,asdefinedbythe2016NLCDlandcoverPrivatemap(Riittersetal.2012).Fivetypesofforestedgewereidentified:forest-developed,forest-agriculture,forest-shrubFIA=ForestInventoryandAnalysis.Sources:Burrilletal.2018;USGS2019a,d.Figure4-10.ProportionofFIAforestlandareaacrosstheconterminousUnitedStatesexhibitingalossofcoreforestcoverstatus—2001to2011.Lossassociatedwithremoval(R;green),stress(S;brown),orfire(F;blue)eventswithina11-acreneighborhood,byforesttypegroupforwesternforesttypegroups(left)andeasternforesttypegroups(right).Theproportionoflossisontheverticalaxis;thesumofproportionsinatypegroupmaybelargerthan1.0becausemorethanonetypeofeventcanbeassociatedwithagivenlossofcoreforeststatus.WesternForestTypeGroupsEasternForestTypeGroupsSources:USGS(2019a,c);Burrilletal.(2018).Removal(R)Stress(S)Fire(F)2020ResourcesPlanningActAssessment4-13&grass,forest-water,andforest-barren.ThemeanshareRPARegionandownerWhilethisanalysisofforestcoverfragmentationdidofeachtype(Riittersetal.2012)indicatestheirrelativenotdistinguishbetweennaturalandanthropogenicimportanceasedgewheretheforestisfragmented,whichfragmentation,separateanalysesofthesamelandcoverdatainturncanindicatethepotentialtypesofecologicalimpacts(Homeretal.2020,Riittersetal.2020)indicatethatalmostoffragmentation(e.g.,FormanandAlexander1998,Murciaallforestcoverlossesandgainsinvolvedtransitionsbetween1995,Ricketts2001).Forexample,nearbyanthropogenicforest,shrub,andgrasslandcovers.Furthermore,mostedge(farms,houses,roads,etc.)tendstoincreasefireforestcovergainsandlossesoccurredinnatural-dominatedignitions(Radeloffetal.2018)aswellasoccurrencesoflandscapes(seetheForestLandscapeContextsectioninvasiveforestplants(Riittersetal.2018)(seealsothebelow)andforestcanopylosseswereassociatedprimarilyDisturbancestoForestsandRangelandsChapter).Exceptwithforestremovalandsecondarilywithfire,stress,orforforest-developededgeinthePacificCoastRegion,landuseconversion(seetheDisturbancestoForestsandalmostallforest-nonforestedgeinthetwowesternregionsRangelandsChapter).Takentogether,thesefindingsareisforest-shrub&grassedge(figure4-11).Mostofthegenerallyconsistentwiththeinterpretationthatmostforestforest-agricultureedgeiscontainedinthetwoeasterncoverlossresultsfrompervasiveforestryoperations(Cohenregions,whichalsoexhibitthelargestpercentagesofforest-etal.2016,Curtisetal.2018,Maseketal.2008).Becausedevelopededge.Forest-agricultureedgeisrelativelymorelossesduetoforestryoperationsintheUnitedStatesareimportantnearnoncorporateprivateforestthanpublicortypicallyfollowedbygainsfromforestregeneration,thatcorporateprivateforest.Therelativelylargesharesofforest-interpretationisstrengthenedforthetwoeasternRPAdevelopededgeinpublicownershipsarelargelyattributableregionsbythebalancebetweendirectgainsandlossestothepresenceofroads(atypeofdevelopment)whichofinteriorforestineachregion(table4-4).Itisplausibletraverserelativelyless-fragmentedforestedlandscapesthattherelativelylargerandcontinuingnetlossofinterior(Riittersetal.2012).areainthewesternRPAregions(table4-3)reflectslowerregenerationfollowingseverewildfireorstress(figure4-10)Figure4-11.Meansharesoffivetypesofforestcoveredgewithina38-acreespeciallyonpubliclands(table4-5).neighborhoodofFIAforestlandplotsacrosstheconterminousUnitedStatesin2016,byRPAregionandownershipcategory.ForestLandscapeContextSources:USGS(2019d);Burrilletal.(2018).TheanthropogeniccontextoflandareaintheconterminousUnitedStateswasevaluatedintermsoflandscapedominanceandinterfacesthatdescribetherelativeimportanceofdevelopedandagriculturelandcoverswithina162-acreneighborhoodofagivenlocation(Riittersetal.2020).Landscapedominanceidentifiesareaswheredeveloped,agriculture,or“natural”(i.e.,allother)landcoversarelocallydominant(atleast60percentoftheneighborhoodarea),whilethelandscapeinterfaceidentifiesareasinwhichdevelopedand/oragriculturelandcoversareasignificantcomponentofthelocallandscape(atleast10percentoftheneighborhoodarea).UsingNLCDdatafrom2001and2016,developedlandincludedthefourNLCDdevelopedclasses(whichincorporatemostoftheimperviousroadcover)andagriculturelandincludedthepasture/hayandcultivatedcropclasses.AllotherNLCDcoverclasseswereconsidered“natural”andthewaterclasswasexcluded.Landscapedominancewasclassifiedas“developed,”“agriculture,”or“natural”ifoneofthethreecorrespondinglandcovertypesexceededthe60percentthresholdvalue,andotherwiseclassifiedas“mixed.”Similarly,landscapeinterfacewasclassifiedas“developed,”“agriculture,”or“both”iftheproportionofthecorrespondinglandcovertype(s)exceededthe10percentthresholdvalue,andotherwiseclassifiedas“neither.”ThesameclassificationswereappliedinthelatersectiononProjectedForestFragmentationandLandscapeContext,butwithadifferentneighborhoodsize.Inthissection,landscapedominance4-14FutureofAmerica’sForestsandRangelandsandinterfacewereevaluatedforalllandareaandforFigure4-13.Netchangeoftotallandareabydominanceclass(left)andforestcoverareaonly,wherethelatterincludedthethreeinterfaceclass(right)from2001to2016,byRPAregion.ChangesoflandNLCDuplandforestclassesandthewoodywetlandsclass.areatoorfromwaterarenotincluded.SeetextfordefinitionsofdominanceAlthoughtheforestinventoryplotdatadescribedabovewereandinterfaceclasses.notusedforthisanalysis,thechanginglandscapecontextofFIAforestlandusehasbeenreportedelsewhere(RiittersandDominanceClassInterfaceClassCostanza2019).Netchange(millionacres)Mostofthetotallandareawasinthenaturaldominanceclassin2016,buttheproportionofareaineachofthePacificCoastRockyMountainNorthSouthdominanceclassesvariedamongRPAregions(figure4-12).Source:USGS(2019a,d).Theproportionoftotalareaindeveloped-andagriculture-dominatedlandscapeswaslargerinthetwoeasternRPAcontextincludedirectchangesduetoforestlossandregionsthaninthetwowesternregions.Inallregions,largergainineachtypeoflandscape,andindirectchangesdueproportionsoftotalareawerecontainedinthedevelopedandtoexpansion(orcontraction)ofeachtypeoflandscapeagricultureinterfacelandscapes,withmorethanhalfofbothtoinclude(orexclude)thepersistentforestarea.InboththeNorthandSouthRegionsoccurringinthoselandscape2001and2016,88percentoftotalforestcoverareawasininterfaces.Followingthepatternsoflandcoverchangefromlandscapesdominatedby“natural”landcovers(table4-6),but2001to2016(table4-2),therewasanetgainofdeveloped31percentwasinlandscapesthatcontainedasignificantsharedominanceandinterfaceareainallRPAregions,anda(atleast10percent)ofdevelopedoragriculturelandcovernetlossofagriculturedominanceandinterfaceareainall(table4-7).From2001to2016,theforestareaindevelopedregionsexcepttheRockyMountainRegion(figure4-13).Indominanceandinterfacelandscapesincreasedby0.4and1.4theRockyMountainRegion,therelativelylargenetlossesmillionacres,respectively,whiletheforestareainagricultureofnaturaldominanceand“neither”interfaceareasareduedominanceandinterfacelandscapesdecreasedby0.8andmoretograsslandconversionthanforestconversionfrom6.1millionacres,respectively.Thechangesintheagriculture2001to2016(Homeretal.2020).Apartfromagriculture-anddevelopedlandscapesweredrivenprimarilybyindirectrelatedchangesintheRockyMountainRegion,mostofthechange.Forexample,thenetrateofforestcoverlosswasnetchangesoccurredinthetwoeasternregions.highestwithinlandscapesdominatedbydevelopedlandcoverAnalogoustotheanalysisofinteriorforestchange,thecomponentsofforestcoverchangeinrelationtolandscapeFigure4-12.Shareoftotallandareabydominanceclass(top)andinterfaceclass(bottom)in2016,byRPAregion.Seetextfordefinitionsofdominanceandinterfaceclasses.Table4-6.Componentsofforestcoverareachangefrom2001to2016intheconterminousUnitedStatesbylandscapedominanceclass.ForestareaNetpercentchangeDominanceclass2016ChangeTotalaDirectbIndirectcmillionacrespercentDeveloped2.60.417.7-8.726.4Agriculture17.0-0.8-4.7-1.0-3.7Natural508.4-13.7-2.6-2.70.1Mixed46.7-1.3-2.8-1.8-1.0Totalforestarea574.7-15.5-2.6-2.6--dSource:USGS(2019d).aPercentchangeofareafrom2001.bForestgainminuslossinapersistentdominanceclass.cDominanceclassgainminuslossofpersistentforest.dNotapplicable.Sources:USGS2019a,d.2020ResourcesPlanningActAssessment4-15Table4-7.Componentsofforestcoverareachangefrom2001to2016intheandrangeland.ThelanduseprojectionsarebasedontheconterminousUnitedStatesbylandscapeinterfaceclass.20RPAscenario-climatefutures(fourRPAscenariosandfiveclimateprojections;seethesidebarRPAScenarios)andForestareaNetpercentchangearethereforeexplicitlylinkedtoprojectedclimatechangeandsocioeconomicchange.MihiarandLewis(inreview)Interfaceclass2016ChangeTotalaDirectbIndirectcprovidedetailsofthemethodsandresults.millionacrespercentAlllandusechangewasassumedtooccuronprivatelyownedlandwithintheselanduseclasses;allotherownerships,asDeveloped33.81.44.4-3.78.1wellasotherNRIcategories(ConservationReserveProgram,water,andotherrural),wereheldconstantthroughouttheAgriculture121.9-6.1-4.8-0.9-3.8projectionperiod.Landdevelopmentisassumedtobeanirreversiblechange—developedlandonlygainsareaoverNeither397.8-10.8-2.6-3.10.4time—becausetherewereonlytrivialhistoricallossesindevelopedareaintheNRIdatausedtocalibratetheBoth21.1--d0.1-2.32.5projectionmodels.ThelanduseprojectionsdonotassumeanysignificantfuturechangeinlandusepolicyorregulationsTotalforestarea574.7-15.5-2.6-2.6--e(i.e.,projectionsarepolicy-neutral,basedonhistoricallanduserelationshipsdrivenbyfutureclimatechangeaswellasaPercentchangeofareafrom2001.populationandeconomicgrowthassumptions).bForestgainminuslossinapersistentinterfaceclass.cInterfaceclassgainminuslossofpersistentforest.ThefutureprojectionsoflandusewerebasedonasubsetdValuebetween-0.05and0.05.ofNRIdataforprivatelandonly,spanning2000to2012.eNotapplicable.Duringthattime,themostactivetransitionsoccurredto/Sources:USGS2019a,d.fromcropandpasturelands(figure4-14).Ofthe6.7millionacresofcroplandmovingtootheruse,67percentofthat(9percent),butthetotalamountofforestareaoccurringinlandwasplacedintheConservationReserveProgramthoselandscapesincreasedby18percentasthedeveloped(CRP).Likewise,91percentofnewcroplandfromtheotherlandsexpandedtoincludeadditionalforestarea.ThenetratecategoryoriginatedfromtheCRP.Theconversiontrendsofforestlosswaslowestinagriculture-dominatedlandscapesofundevelopedlandintodevelopedlandhavechanged(1percent),butthetotalforestareainthoselandscapessignificantlythroughtime(figure4-3).Approximatelydecreasedby5percentasagriculturallandscontractedto1.2millionacresofundevelopedlandtransitionedintoexcludeadditionalforestarea.Incontrast,thelocationsofdevelopedlandannuallyinthe1980s;thisamountincreasednatural-dominatedandnoninterfacelandscapeswererelativelytoapproximately2.0millionacresperyearbetween1992stableandtheforestchangewithinthoselandscapeswasand1997,buttherateofnewlydevelopedlanddeclineddrivenprimarilybydirectforestlossandgain.thereafter(figure4-3).Bigelowetal.(2022)foundthatthedeclinewasconsistentacrossurbanandruralregionsinProjectedLandUsetheconterminousUnitedStatesandresultedin7.0millionacresofforestandagriculturelandremainingundeveloped❖Developedlandareaisprojectedtoincreaseinbetween2000and2015.Ifdevelopedlandhadcontinuedtoexpandatthesamerateobservedbefore2000,thosethefuture,whileallnon-developedlandusesare7.0millionacresofforestandagricultureusewouldhaveprojectedtolosearea.Themostcommonsourceconvertedtoadevelopeduse.ofnewdevelopedlandisforestland.Theprojectionsarebasedonlandusetransitionprobabilities,❖ForestlandareaisprojectedtodecreaseunderestimatedfromNRIplotswithrepeatedobservationsduringtheyears2000to2012(MihiarandLewis,inreview).Theallscenarios,althoughatlowerratesthanmodelingapproachhasthreecomponents:(a)developingprojectedbythe2010Assessment.empiricallinkagesbetweenclimate,population,income,andthevalueoflandinproductionforthemajorU.S.land❖Higherprojectedpopulationandincomegrowthusesofagriculture(cropandpasture),forest,anddeveloped;(b)estimatinganempiricallinkbetweenthenetreturnstoleadtorelativelylessforestland,whilehottereachlanduseandtheobservedchoiceoflanduseacrossprojectedfutureclimatesleadtorelativelymoreagriculture,forest,anddevelopedconditionalonthecurrentforestland.landuseallocation;and(c)usingestimatedtransitionprobabilitiestoprojectfuturelandusechanges.❖ProjectedfuturelandusechangeismoresensitivetothevariationineconomicfactorsacrossRPAscenariosthantothevariationamongclimateprojections.LandUseChangeModelLandusechangeisamajordriverofresourcechange.WeprojectedlandusechangeonprivatelandforeachcountyintheconterminousUnitedStatesfrom2020to2070forfivemajorlanduseclasses:forest,developed,crop,pasture,4-16FutureofAmerica’sForestsandRangelandsFigure4-14.GrosslandusechangeintheconterminousUnitedStatesfromgainindevelopedlandandlargestnetlossinforestland,2000to2012.Forlandmovingoutofaparticularlandusein2000(barsonwhiletheHLscenarioresultedinthesmallestnetgaininleft),thewidthofthegrayflowsindicatetherelativeareamovingintoeachdevelopedlandandsmallestnetlossinforestland(table4-9),suggestingthatthelandusechangemodel(Mihiarandnewusein2012(barsonright).Lewisinreview)ismoresensitivetothevariationinfutureeconomicvariables(populationandincome)thaninfutureatmosphericwarmingandclimatevariables(temperatureandprecipitation)acrossRPAscenario-climatefutures.Figure4-15.Projectednetlandusechangesfrom2020to2070acrosstheconterminousUnitedStates,byRPAscenario.Therangedrawnwithineachbarrepresentsdifferenceinprojectionacrossclimateprojections.60Changeinmillionsofacres40200-2020002012DevelopedCropPastureRangelandSource:USDA2015.ForestMajorLandUseLandUseProjectionsRPAScenarioLMHLHMHHOuranalysesofthelanduseprojectionsarestratifiedacrossLM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highseveraldimensions.Weexaminebothgrossandnetlandwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.usechange.Grosschangedescribesalltransitionsoflandbetweenuses,whilenetchangedescribesthechangeinLanduseprojectionsrevealanexpansionofdevelopedlandareaafteraccountingforalltransitionsinandoutoflandof41.3to57.0millionacresacrosstheRPAscenario-thatlanduse.Wealsoconsiderhowtheprojectionsdifferclimatefutures(table4-9).However,thoseincreasesdifferacrosstheRPANorth,South,RockyMountain,andPacificbyRPAregion(figure4-18).ThelargestprojectedgrowthCoastRegions.Finally,weexploretheprojectionsacrossindevelopedlandareaisintheSouthRegion,wherethefourRPAscenariosandfiveclimateprojections(seeapproximately18.4(HL-hot)to25.0millionacres(HH-thesidebarRPAScenarios).Weexaminetheinfluenceofwet)ofnewdevelopedlandisprojected.TheNorthRegionatmosphericwarmingbycomparingresultsfromthelowerhasthesecondlargestprojectedincreaseindevelopedland,warming-moderategrowthRPAscenario(LM)tothehighapproximately10.6(HL-hot)to14.0millionacres(HH-warming-moderategrowthscenario(HM),andweexamineleastwarm).TheRockyMountainRegionisprojectedtotheinfluenceofsocioeconomicgrowthbycomparingtheseedevelopedlandareagrowbetween6.4millionacreshighwarming-lowgrowthRPAscenario(HL)tothehigh(HL-hot)and8.9millionacres(HH-dry),andthePacificwarming-highgrowthscenario(HH).Inaddition,theCoastRegionisprojectedtoseedevelopedlandareagrowinfluenceoffutureclimateisexaminedbycomparingresultsbybetween5.9millionacres(HL-hot)and9.9millionacresacrosstheselectedclimateprojections.(HH-leastwarm).TheseprojectedchangesofdevelopedlandareaareimportanttounderstandhowfutureforestedProjectedtrendsinlandusefrom2020to2070areconsistentlandscapesmayevolve,becauselossofforestlandisacrossRPAscenarios,indicatinglargenetincreasesinprojectedtobethelargestsourceofnewdevelopedland,developedlandandmoderatenetdeclinesineachoftheaccountingforanaverageof46percentofnewdevelopednon-developedlanduses(figure4-15).Projecteddeclinesland(table4-10).arelargestincropuseandsmallestinrangelanduseforeachscenario.TheHHscenarioresultedinthelargestnet2020ResourcesPlanningActAssessment4-17RPAScenariosTheRPAAssessmentusesasetofscenariosofcoordinatedFigure4-16.Characterizationofthe2020RPAAssessmentfutureclimate,population,andsocioeconomicchangescenariosintermsoffuturechangesinatmosphericwarmingandtoprojectresourceavailabilityandconditionovertheUnitedStatessocioeconomicgrowth.Thesecharacteristicsarenext50years.ThesescenariosprovideaframeworkforassociatedwiththefourunderlyingRepresentativeConcentrationobjectivelyevaluatingaplausiblerangeoffutureresourcePathway(RCP)–SharedSocioeconomicPathway(SSP)outcomes.combinations.The2020RPAAssessmentdrawsfromtheglobalSource:Langneretal.(2020).scenariosdevelopedbytheIntergovernmentalPanelonClimateChangetoexaminethe2020to2070timeperiod(IPCC2014).TheRPAscenariospairtwoalternativeclimatefutures(RepresentativeConcentrationPathwaysorRCPs)withfouralternativesocioeconomicfutures(SharedSocioeconomicPathwaysorSSPs)inthefollowingcombinations:RCP4.5andSSP1(lowerwarming-moderateU.S.growth,LM),RCP8.5andSSP3(highwarming-lowU.S.growth,HL),RCP8.5andSSP2(highwarming-moderateU.S.growth,HM),andRCP8.5andSSP5(highwarming-highU.S.growth,HH)(figure4-16).Thefour2020RPAAssessmentscenariosencompassmostoftheprojectedrangeofclimatechangefromtheRCPsandprojectedquantitativeandqualitativerangeofsocioeconomicchangefromtheSSPs,resultinginfourdistinctfuturesthatvaryacrossamultitudeofFigure4-17.Characteristicsdifferentiatingthe2020RPAAssessmentscenarios.ThesecharacteristicsareassociatedwiththefourunderlyingRepresentativeConcentrationPathway(RCP)–SharedSocioeconomicPathway(SSP)combinations.4-18FutureofAmerica’sForestsandRangelandscchhaarraaccteterrisistitcicss((fifgiguurree44--1177)),,aannddpprroovvididininggaauunnififyyininggcclilmimaateteffuututurreessffoorrththeeccoonnteterrmmininoouussUUnnitieteddSStatatetess((tatabbleleffrraammeewwoorrkkththaattoorgrgaannizizeessththeeRRPPAAAAssseesssmmeennttnnaatuturraall44--88));;hhoowweevveer,r,cchhaarraaccteterrisistitcicssccaannvvaarryyaattfifnineerrssppaatitaiallssccaaleless..rreessoouurrcceesseecctotorraannaalylysseessaarroouunnddaaccoonnssisistetennttsseettooffppoosssibibleleAAltlhthoouugghhththeessaammeemmooddeelslswweerreesseeleleccteteddtotoddeevveeloloppcclilmimaatetewwoorrldldvvieiewwss..TThheeSScceennaarrioiossCChhaappteterrddeessccrribibeesshhoowwththeesseepprroojejecctitoionnssffoorrbbooththlolowweerraannddhhigighh--wwaarrmmininggffuututurreess,,sscceennaarrioiosswweerreesseeleleccteteddaannddppaairireedd;;mmoorreeddeetatailislsaarreeddisistitninccttcclilmimaatetepprroojejecctitoionnssffoorreeaacchhmmooddeellaarreeaasssoocciaiateteddpprroovvidideeddininLLaannggnneerreettaal.l.((22002200))..wwitihthRRCCPP44.5.5aannddRRCCPP88.5.5..TThheeSScceennaarrioiossCChhaappteterrddeessccrribibeesshhoowwththeesseecclilmimaatetemmooddeelslswweerreesseelelecctetedd..JJooyycceeTThhee22002200RRPPAAAAssseesssmmeennttppaairirssththeesseeffoouurrRRPPAAsscceennaarrioiossaannddCCoouulslsoonn((22002200))ggiviveeaammoorreeeexxtetennssiviveeeexxpplalannaatitoionn..wwitihthfifviveeddififeferreennttcclilmimaatetemmooddeelslsththaattccaapptuturreeththeewwidideerraannggeeooffpprroojejeccteteddffuututurreetetemmppeerraatuturreeaannddpprreeccipipitiatatitoionnTThhrroouugghhoouuttththeeRRPPAAAAssseesssmmeennt,t,ininddivivididuuaallsscceennaarrioio--aaccrroosssththeeccoonnteterrmmininoouussUUnnitieteddSStatatetess..AAnneennsseemmbblelecclilmimaateteffuututurreessaarreerreeffeerrreeddtotobbyyppaairirininggRRPPAAsscceennaarrioiosscclilmimaatetepprroojejecctitoionnththaattaavveerraaggeessaaccrroosssththeemmuultlitpiplelewwitihthsseeleleccteteddcclilmimaatetepprroojejecctitoionnss..FFoorreexxaammpplele,,aannaannaalylyssisismmooddeellpprroojejecctitoionnssisisnnoottuusseeddbbeeccaauusseeooffththeeimimppoorrtatanncceerruunnuunnddeerr““HHLL--wweet”t”aasssuummeessaaffuututurreewwitihthhhigighhaatmtmoosspphheerricicooffpprreesseerrvvininggininddivivididuuaallmmooddeellvvaarriaiabbiliiltiytyffoorrrreessoouurrcceewwaarrmmininggaannddlolowwUU.S.S..ppooppuulalatitoionnaannddeeccoonnoommicicggrroowwththmmooddeelilninggeeffoforrtsts..TThheefifviveecclilmimaatetemmooddeelslssseeleleccteteddbbyyRRPPAA((HHLLRRPPAAsscceennaarrioio)),,aasswweelllaassaawweetteterrcclilmimaateteffoorrththeerreepprreesseennttleleaassttwwaarrmm,,hhoot,t,ddrryy,,wweet,t,aannddmmididddlele--ooff--ththee--rrooaaddccoonnteterrmmininoouussUUnnitieteddSStatatetess((wweettcclilmimaatetepprroojejecctitoionn))..TTaabblele44-8-8..FFiviveecclilmimaatetemmooddeelslsseseleleccteteddtotorereflfeleccttththeerarannggeeooffththeefufullllsesettooff2200cclilmimaatetemmooddeelslsininththeeyyeeaarr22007700..EEaacchhmmooddeellwwaassrurunnuunnddeerrRRCCPP44.5.5aannddRRCCPP88.5.5,,pprorovvididininggaararannggeeooffddififefererennttUU.S.S..cclilmimaatetepprorojejecctitoionns.s.CClilmimaatetemmooddeellLLeeaaststwwaarrmmHHoottDDrryyWWeettMMididddleleInInstsittiututitoionnIPIPSSLL-C-CMM55AA-M-MRRNNoorErESSMM11-M-MMMRRI-IC-CGGCCMM33HHaaddGGEEMM22-E-ESSCCNNRRMM-C-CMM55InInstsittiututtPPieierrereSSimimoonnNNoorwrweeggiaiannCClilmimaateteMMeeteteoororolologgicicaallMMeettOOfffifciceeHHaaddleleyyLLaapplalaccee,,FFraranncceeNNaatitoionnaallCCeenntrtereooffCCeennteter,r,NNoorwrwaayyRReeseseaarcrchhCCeenntrtere,,UUnnitieteddMMeeteteoororolologgicicaallRReeseseaarcrchh,,KKininggddoommInInstsittiututete,,JaJappaannFFraranncceeRRCCPP==RReperperseesnetnattaitvieveCConocnecnetnrtartaitoinonPPatahtwhwaya.y.SoSuorucrec:e:JoJyocyeceanadndCCouoluslosnon2022002.0.OOvveerrththee5500--yyeeaarrppeerrioioddffrroomm22002200toto22007700,,wweepprroojejeccttaaFFigiguurree44-1-188..PProrojejeccteteddnneettddeevveeloloppeeddlalanndduusesecchhaannggeefrforomm22002200toto22007700,,bbyytototatallnneettffoorreessttlalannddlolosssooffbbeetwtweeeenn77.6.6aanndd1155.0.0mmilililoionnRRPPAArereggioionnaannddRRPPAAscsceennaariroio..TThheerarannggeeddrarawwnnwwitihthinineeaacchhbbaarrrereppreresesenntstsaaccrreess((tatabblele44--99))..WWhheennaavveerraaggininggrreessuultlstsaaccrroosssRRPPAAddififefererenncceeininpprorojejecctitoionnaaccrorossscclilmimaatetepprorojejecctitoionns.s.sscceennaarrioio--cclilmimaateteffuututurreess,,aapppprrooxximimaatetelyly9911ppeerrcceennttooffccuurrreennttffoorreessttlalannddisispprroojejeccteteddtotorreemmaaininininffoorreessttuusseebbyy22007700((tatabblele2544--1100))..MMoossttooffththeeggrroosssffoorreessttlolosss((1199.8.8toto2266.0.0mmilililoionnaaccrreess))isispprroojejeccteteddtotoccoonnvveerrtttotoddeevveeloloppeeddlalanndd((tatabblele44--1111)),,Changeinmillionsofacres20wwhhicichhisisaasssuummeeddtotobbeeaappeerrmmaanneennttcchhaannggee,,ffoollolowweeddbbyyccoonnvveerrssioionnsstotoppaasstuturree,,ccrroopp,,aannddrraannggeelalanndd((tatabblele44--1111))..15WWhheennaavveerraaggininggrreessuultlstsaaccrroosssRRPPAAsscceennaarrioio--cclilmimaateteffuututurreess,,wweepprroojejeccttaabboouutt2255.3.3mmilililoionnaaccrreessooffnneewwffoorreessttlalannddwwilill10bbeeaaddddeeddffrroommccoonnvveerrssioionnssoouuttooffppaasstuturreelalanndd((1177.4.4mmilililoionn)),,ccrroopplalanndd((22.4.4mmilililoionnaaccrreess)),,aannddrraannggeelalanndd((55.5.5mmilililoionnaaccrreess))5((tatabblele44--1100))..TTrraannssitiitoionnssbbeetwtweeeennffoorreessttaannddppaasstuturreelalannddssaarreeththeemmoossttccoommmmoonnaannddaaccccoouunnttffoorrththeelalargrgeessttaarreeaaooffggrroosss0ffoorreessttcchhaannggee..OOnnlylyccoonnvveerrssioionnssffrroommffoorreesstttotoddeevveeloloppeeddaannddppaasstuturreetotoffoorreessttsshhoowwssigignnifiifcicaannttvvaarriaiatitoionnininpprroojejecctitoionnaaccrroosssPacificCoastRockyMountainNorthSouthRRPPAAsscceennaarrioio--cclilmimaateteffuututurreess((tatabblele44--1111))..TThheerreemmaaininininggccoonnvveerrssioionntytyppeessaarreennoottsseennssitiitviveetotosscceennaarrioiossoorrcclilmimaateteRPARegionpprroojejecctitoionnss,,vvaarryyininggbbyylelesssththaann11.0.0mmilililoionnaaccrreessaaccrroossssscceennaarrioiossaannddcclilmimaatetepprroojejecctitoionnss..RPAScenarioLMHLHMHHLLMM==lolwowererwwaramrminign-gm-modoedreartaeteUU.S..Sg.rgorwowtht;h;HHLL==hihgihghwwaramrminign-gl-olwowUU.S..Sg.rgorwowtht;h;HHMM==hihgihghwwaramrminign-gm-modoedreartaeteUU.S..Sg.rgorwowtht;h;HHHH==hihgihghwwaramrminign-gh-ihgihghUU.S..Sg.rgorwowtht.h.22002200RReessoouurcrceessPPlalannnnininggAAccttAAsssseessssmmeenntt44--1199Table4-9.Projectednetlandusechangefrom2020to2070byRPAscenarioandclimateprojection.LMscenarioHMscenarioClimateprojectionClimateprojectionLeastHotDryWetMiddleLeastHotDryWetMiddlewarmwarmLandusemillionacres(percent)-12.6millionacres(percent)-12.1Forest-13.0(-3.1%)-12.5(-3.0%)Developed(-3.2%)-11.9-11.9-12.5(-3.0%)-8.6-11.8-11.9Crop(-2.9%)(-2.9%)(-3.0%)50.7(-2.1%)(-2.9%)(-2.9%)48.9Pasture51.8(51.9%)50.2(50.1%)Rangeland(53.1%)49.150.751.6(51.3%)43.949.050.1(50.4%)(51.9%)(52.8%)-19.5(45.0%)(50.2%)(51.3%)-19.3-20.6(-5.4%)-19.2(-5.4%)(-5.8%)-20.4-23.4-24.4-10.9(-5.3%)-26.9-19.7-23.2-10.3-10.6(-5.7%)(-6.5%)(-6.8%)(-9.7%)(-7.5%)(-5.5%)(-6.5%)(-8.6%)(-8.9%)-11.1-9.7-7.8-7.6-7.8(-9.3%)-3.7-9.5-8.0-7.3-7.6(-8.1%)(-6.5%)(-6.4%)(-1.9%)(-3.1%)(-7.9%)(-6.7%)(-1.8%)(-1.9%)-7.5-7.1-7.6-7.1(-1.8%)-4.6-8.0-6.9Middle(-1.8%)(-1.9%)(-1.7%)(-1.1%)(-2.0%)(-1.7%)-14.5HLscenarioHHscenario(-3.5%)ClimateprojectionClimateprojection55.3LeastHotDryWetMiddleLeastHotDryWet(56.6%)warmwarmLandusemillionacres(percent)-11.0millionacres(percent)-20.8Forest-11.3(-2.7%)-15.0(-5.8%)Developed(-2.8%)-7.6-10.7-10.8(-3.7%)-10.8-14.3-14.5Crop(-1.9%)(-2.6%)(-2.6%)46.0(-2.6%)(-3.5%)(-3.5%)-11.4Pasture47.1(47.2%)57.0(-9.5%)Rangeland(48.3%)41.346.147.0(58.3%)49.855.657.0(42.4%)(47.3%)(48.2%)-18.6(51.1%)(57%)(58.3%)-8.7-18.4(-5.2%)-20.8(-2.2%)(-5.1%)-26.4-19.0-22.5(-5.8%)-28.3-21.3-24.9-10.6(-7.3%)(-5.3%)(-6.3%)-9.8-12.3(-7.9%)(-5.9%)(-6.9%)(-8.8%)(-8.2%)(-10.3%)-3.3-9.0-7.5-4.8-10.6-9.2-6.8(-2.7%)(-7.5%)(-6.2%)-6.6-9.0(-4.1%)(-8.9%)(-7.7%)(-1.7%)(-1.6%)(-2.2%)-4.0-7.4-6.3-5.9-9.5-8.4(-1.0%)(-1.8%)(-1.6%)(-1.5%)(-2.3%)(-2.1%)LM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.Note:Differenceswithvaluescalculatedfromtable4-11areduetorounding.Table4-10.Projectedgrosslandusechangefrom2020to2070,averagedoverallRPAscenariosandclimateprojections.2070landuse(millionacres)ForestDevelopedCropPastureRangeland2020total372.12.2409.8Forest23.23.68.7-97.7Developed-4.0358.82020landuseCrop2.497.7--6.2119.4(millionacres)Pasture17.4382.5402.2Rangeland5.510.6270.171.7395.2-2070total397.4-7.3Mean50-year-12.48.159.428.3-netchange(-3.0%)(-1.8%)8.83.91.5147.6336.9110.650.7-21.8-9.2(+51.9%)(-6.1%)(-7.7%)Note:Themeannetchangesshownherearenotstrictlycomparabletovaluesshownintables4-9and4-11.4-20FutureofAmerica’sForestsandRangelandsChangeofforesttodevelopedlandrangesfrom19.8millionhigheratmosphericwarmingresultsinmoreforestlandandacres(HL-hot)to26millionacres(HH-leastwarm)acrosslesscroplandacrosstheUnitedStates.RPAscenario-climatefutures(table4-11).Largelybecauseoftheselossestodevelopedland,theseRPAscenario-climatePasturetoforestlandtransitionsaccountforthegreatestfuturesarealsoresponsiblefortheoverallsmallest(34.4amountofnewforestlandinthefuture,between17.2andmillionacres)andlargest(40.5millionacres)grosslossesof18.2millionacres,followingasimilarpatterntothatofforestland.GrossgainsofforestlandarelowestunderHH-croptoforestlandtransitions(table4-11).Whencomparingmiddle(24.9millionacres)andhighestunderHM-hot(26.5resultsusingthehotclimateprojection,weproject1.0millionacres),withmostgainscomingfrompasturelandmillionacresofadditionalforestfrompasturelandundertheacrossallscenario-climatefutures.HMscenariorelativetoLM.WhencomparingresultsacrossclimateprojectionsundertheHMscenario,weproject0.9TheprojectionsforcroptoforestlandtransitionsarerelativelymillionadditionalacresconvertingtoforestfrompasturestableacrossRPAscenarios(table4-11).However,underforthehotclimateprojectionrelativetotheleastwarmthehigherwarmingRPAscenarios(i.e.,HL,HM,andHH),projection.Ourlanduseprojectionsindicatethathotterthelargestdifferenceingrosschangeofcroptoforestareaisfuturetemperaturesmayleadtomoreforestlandandlessprojectedbetweentheleastwarmandhotclimateprojections.pastureland.Weprojectapproximately0.5millionacresofadditionalforestareaconvertingfromcroplandwhencomparingtheTheprojectedreductionsinforestlandarea,whichoccuronleastwarmtothehotprojections.Wealsoprojectabout0.4privatelandsunderallRPAscenarios,differbyRPAregionmillionacresofadditionalforestareaconvertingfromcropalthoughlossesarealwayshighestundertheHH-leastwarmlandundertheHMscenariorelativetotheLMscenario,bothscenario-climatefuture(figure4-19).Projectedforestusingthehotclimateprojection.TheseresultssuggestthatlandlossesarelargestintheSouthRegion—between4.6million(HL-hot)and9.2millionacres(HH-leastwarm).Table4-11.Projectedgrossforestlandchangefrom2020to2070,byRPAscenarioandclimateprojection.LMscenarioHMscenarioClimateprojectionClimateprojectionLeastHotDryWetMiddleLeastHotDryWetMiddlewarmwarmGrossforestlossmillionacres23.4millionacres22.9Foresttodeveloped24.03.623.43.6Foresttocrop3.622.823.423.88.73.620.722.823.38.7Foresttopasture8.72.28.72.2Foresttorangeland2.23.63.53.52.23.63.63.5Grossforestgain2.32.3Croptoforest2.38.78.78.717.22.38.88.78.717.2Pasturetoforest17.35.517.35.5Rangelandtoforest5.52.22.22.25.52.22.22.2Middle2.42.52.52.82.42.525.217.217.617.418.217.217.53.68.75.55.55.55.55.55.52.2HLscenarioHHscenario2.3ClimateprojectionClimateprojection17.15.5LeastHotDryWetMiddleLeastHotDryWetwarmwarmGrossforestlossmillionacres21.8millionacresForesttodeveloped22.33.626.0Foresttocrop3.619.821.722.28.73.622.925.225.8Foresttopasture8.72.28.7Foresttorangeland2.23.63.63.52.23.63.63.5Grossforestgain2.3Croptoforest2.38.88.78.717.22.38.78.78.7Pasturetoforest17.45.517.3Rangelandtoforest5.52.22.22.25.52.22.22.22.72.42.52.72.42.418.217.217.518.217.117.45.55.55.55.55.55.5LM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.Notes:Therearenotransitionsfromdevelopedtoforestland.Thesumoftheroundedgrosschangesshownheremaydifferfromthenetchangesshownintable4-9.2020ResourcesPlanningActAssessment4-21ThePacificCoastRegionisprojectedtolosebetween2.5Figure4-19.Projectedforestlandnetchangefrom2020to2070,byRPAmillion(LM-wet)and3.1million(HH-leastwarm)acresofregionandRPAscenario.Therangedrawnwithineachbarrepresentsforestlandarea,andtheNorthRegionisprojectedtolosedifferenceinprojectionacrossclimateprojections.between1.6million(LM-dry)and2.2million(HH-leastwarm)acres.TheRockyMountainRegionisprojectedto0.0loselessthan0.5millionacresunderallRPAscenario-climatefutures.ThelargeprojectedlossesintheSouthChangeinmillionsofacres-2.5Regioncanbeexplainedbyboththelargeinitialbaseofforestareaandthelargeprojectedgainsindevelopedland-5.0area,mostlyderivingfromforestland.ThesmallprojectedforestlossesintheRockyMountainRegionareexplained-7.5byitsmuchsmallerinitialbaseofforestarea,andbytheprojectionthatrangelandisthedominantsourceofnewPacificCoastRockyMountainNorthSouthdevelopedlandinthisregion.RPARegionToexaminetheimpactoffutureatmosphericwarmingonRPAScenarioLMHLHMHHfuturelandusechange,wecomparedthelowerwarmingLMandhighwarmingHMRPAscenarios(table4-9),LM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwherewarmingvariesacrossscenariosbuteconomicwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.growthissimilar.Theaveragenetincreaseindevelopedlandareais52.0percentacrossthefiveclimateprojectionsundertheHHscenario(by2.2millionand1.6millionundertheLMscenario,whilethecorrespondingaverageacres,respectively).Ourresultssuggestthatscenariosis49.6percentundertheHMscenario,adifferenceof2.4assuminghigheratmosphericwarmingreducetheprojectedpercent.ThedifferencebetweentheLMandHMscenariosexpansionofdevelopedlandarea,whilescenariossuggeststhatafuturewithhigheratmosphericwarmingassuminghighergrowthinpopulationandincomehavetheavoidsamoderateamountofnewdevelopmenttotheoppositeimpact.Thisresultissupportedbyanextensivebenefitofnon-developedlanduses.SlightdifferencesinanalysisoftheimpactofclimateonlandusechangesocioeconomicprojectionsbetweenLMandHMmayalsoconductedbyMihiarandLewis(inreview).playaroleinthedifferingoutcomesforlanddevelopmentfoundinourprojections.However,ananalysiswhereThisanalysisprojected50-yearnetlandusechangessocioeconomicprojectionswereheldconstantalsothataresignificantlydifferentfromtheprojected50-yearfoundlowerdevelopmentratesassociatedwithahighernetchangesreportedinthe2010RPAAssessment.Inwarmingfuture(MihiarandLewisinreview).Avoided-particular,the2010RPAAssessmentprojectedanaveragedevelopmentundertheHMscenarioprimarilyaffectsincreaseindevelopedlandareabetween39and69millionforestland,resultinginapproximately1.2millionacresofacresfrom2010to2060,whileweprojectanincreaseadditionalforestby2070.Thehigherwarmingfuturealsoindevelopmentrangingfrom43.9to57.0millionacresbenefitspastureland,withprojectionsfortheHMscenariofrom2020to2070.Similarly,the2010RPAAssessmentresultingin0.8millionacresmorepasturelandthantheprojecteda50-yearaveragelossinforestlandrangingfromLMscenario.16to34millionacresby2060,whereasweprojecta50-yearlossinforestarearangingfrom10.7to15.0millionToexaminetheimpactofeconomicgrowthonfuturelandacresby2070.Thedifferenceinprojecteddevelopedlandusechange,wecomparedthelowgrowthHLandhighareachangeislikelyduetothedecliningannualrateofgrowthHHRPAscenarios(table4-9),whereeconomicnewdevelopedlandwhichbeganaroundtheyear2000growthvariesacrossscenarios,butatmosphericwarming(figure4-3).The2010RPAAssessmentprojectionswereremainsconstant.Theinfluenceofeconomicgrowth,basedonNRIdatafrom1987to1997anddidnotreflectrepresentedbypopulationandincomeprojections,onthedecliningannualrateafter2000.newdevelopedlandfarsurpassestheinfluenceoffuturewarmingdescribedabovewhencomparingtheLMandHMscenarios.Theaveragenetexpansionofdevelopedlandarea(acrossthefiveclimateprojections)is46.7percentundertheHLscenario,whilethecorrespondingaverageis56.3percentundertheHHscenario—adifferenceof9.4percent.Forestlandisprojectedtobe3.5millionacreslowerundertheHHscenariothantheHLscenario,andcropandpasturelandsarealsoprojectedtobelower4-22FutureofAmerica’sForestsandRangelandsProjectedTreeandImperviousdataunderestimatestreecover(NowakandGreenfieldCoverChange2010),weappliedsimilarphotointerpretation(PI)methodsto4,000randompointsacrosstheconterminousUnited❖ProjectionsoftreeandimperviouscoverwereStatestoestimatetreeandimperviouscoverwithinRPAlanduseclassesandcomparethemwithTCCestimates.generallyconsistentamongthreerepresentativeTherewasnostatisticallysignificantdifferencebetweenPDIscenarioswhichallindicatedanincreaseinandPIvaluesforimperviouscover;however,theTCCdataimperviouscoverandaslightincreaseintreeunderestimatedPItreecoverbyanaverageof10.8percentcovernationally.(table4-12).Anadjustmentfactor(table4-12)wasusedtoadjusttreecoverforeachTCCpixelestimate.AdjustedTreeandimperviouscoverchangealongsidechangesintreecover,hereafterreferredtoastreecover,wasthenlanduse.TreecoverisoneofthesimplestproxiesforcalculatedforeachRPAlandcoverclassineachcountyofassessingtheamountofforestanditsassociatedbenefits,theconterminousUnitedStates.forexamplemoderatingclimate,reducingbuildingenergyuseandatmosphericcarbondioxide(CO2),providingwoodForprojections,thetreecanopycoverestimatedfromtheproducts,improvingairandwaterquality,mitigatingrainfall2016datawasusedasthe2020basetreecoverestimate.runoffandflooding,providingwildlifehabitat,enhancingForeachsubsequentdecadefrom2030to2070,thehumanhealthandsocialwell-being,andloweringnoiseprojectedareaofeachlanduseclasswasmultipliedbyimpacts(NowakandDwyer2007).Airpollutionremovalthecounty-specificpercenttreeandimperviouscoverofbyconterminousUnitedStatestreesandforestsin2010thecorrespondinglandcoverclasstoestimatethetreewasestimatedat19.2milliontons,withhealtheffectsandimperviouscoverineachcounty.Ifacountywasvaluedat$6.8billion(Nowaketal.2014).Thesepollutantsmissingalandcoverclassin2020,thecovervaluesfromaare:carbonmonoxide(CO);nitrogendioxide(NO2);neighboringcountywereused.Thisprocessassumedthatozone(O3);lead(Pb);sulfurdioxide(SO2)andparticulatetheaveragetreeandimperviouscoversin2020foreachlandmatter(PM),whichincludesparticulatematterlessthan10coverclassatthecountylevelremainconstantthroughtime,microns(PM10)andparticulatematterlessthan2.5micronswiththelanduseclassareachangingthroughtime(Nowak(PM2.5)inaerodynamicdiameter.Acriticalquestionrelatedetal.1996).toforestsustainabilityishowtreecoverislikelytochangegivenprojectedlandusechanges.ByestimatingthepotentialThreeofthe20RPAscenario-climatefutureswereselectedchangeintreecoveracrosstheconterminousUnitedStates,formappingandanalysisofprojectedcoverchanges:forestmanagementplanscanbedevelopedtoprovidedesiredlevelsoftreecoverandforestbenefitsforcurrent•Averagescenario(HM-wet).Thenationalaveragetreeandfuturegenerations.coverincreasewasclosesttotheaveragechangeamongallImpervioussurfaces(suchasroadsandbuildings)changeRPAscenario-climatefutures.alongsidelandandtreecoverchange.Impervioussurfacesprovideessentialservicestosociety,buttheycanalso•Maximumscenario(HL-hot).Thescenariohadthenegativelyimpacttheenvironmentthroughincreasedairtemperaturesandheatislands(HeislerandBrazel2010,highestaverageincreaseintreecover.Oke1989).Theseenvironmentalchangesconsequentlyaffectbuildingenergyuse,humancomfortandhealth,ozoneTable4-12.ComparisonofUSDAForestServicetreecanopycoverandproduction,andpollutantemissions.Inaddition,imperviousphoto-interpretedpercenttreecanopycoverestimatesbyRPAlandusesurfacessignificantlyaffecturbanhydrology(e.g.,streamclass.flow,waterquality)(NationalResearchCouncil2008,USEPA1983).Landuse2016TCC2016PIDifferenceaAdjustmentclassfactorbTheprojectedlandusechangesinthe20RPAscenario-58.975.4-16.50.401climatefutures(seethesidebarRPAScenarios,above)Forest16.131.6-15.50.185wereusedtoestimatechangesintreeandimperviouscoverDeveloped2.28.0-5.80.059between2020and2070.Thebaselineamountof2020treeCrop14.225.6-11.40.132andimperviouscoverineachlandcoverclassofeveryPasture2.610.9-8.30.085countyintheconterminousUnitedStateswascalculatedOther0.45.6-5.20.052usingthe2016USDAForestServiceTreeCanopyCoverWater21.832.7-10.8na(TCC)dataset(USDAForestService2019)andtheNLCDAllclasses2016PercentDevelopedImperviousness(PDI)dataset(MRLC2021).Becausethe2001NLCDtreecanopycoverAF=adjustmentfactor;NLCD=NationalLandCoverDatabase;PI=photo-interpreted;TCC=treecanopycover.aDifferenceinpercenttreecover(TCCminusPI).Alldifferencesaresignificantatalpha=0.05.bAdjustmentfactorusedtoadjustTCCtreecoverestimates;AF=-difference/(100-NLCDtreecover).2020ResourcesPlanningActAssessment4-23•Minimumscenario(HH-middle).ThescenariohadtheFigure4-20.TreecoverchangeforthreeRPAscenariosfrom2020to2070.lowestaverageincreaseintreecover.Average(HM-wet)scenarioProjectedchangesintreeandimperviouscoverweresummarizedbyState,RPAregion,andecoregion(i.e.,forest,desert,grassland)(NatureConservancy2018).ProjectedTreeCoverChangeMaximum(HL-hot)scenarioMinimum(HH-middle)scenarioWhilethenationalaveragetreecoverdidnotchangemuchamongthethreescenarios,therewereregionallyconsistentdifferencesintreecoverchange(figure4-20).Theoverallprojectednationalincreaseintreecoverbetween2020and2070intheaveragescenariowas0.02percent.AreasprojectedtohavetreecoverincreaseswereincentralFlorida,California,Texas,andOklahoma;easternWashington,Colorado,andArkansas;southernMinnesota,Wisconsin,andMichigan;northernMissouri;westernNewYork,Ohio,Kentucky,andTennessee;andIllinoisandIndiana.TreecoverlosswasprojectedinNewEngland;muchoftheSoutheasternUnitedStates;northernMinnesota,Wisconsin,Idaho,andLouisiana;southernMissouri;easternTexas,Oklahoma,andKansas;andwesternArkansas,Washington,andOregon(figure4-20).CountiesthathadthelargestprojectedincreasesintreecoverweretypicallyintheRPASouthRegion.Thecountieswiththelargestdecreasesintreecoverwereallcity-basedcountiesinVirginia(table4-13),whichareallmuchsmallerthanthetypicalU.S.countyandtendtobuildoutwiththedevelopedlandusewithintheirboundariesby2070.Overall,theStateswiththelargestprojectedincreasesintreecoverwereDelaware(+0.9percent),Indiana(+0.9percent),andIllinois(+0.7percent);greatestreductionsintreecoverTable4-13.TopfivecountiesintheconterminousUnitedStateswiththegreatestprojectedincreasesanddecreasesintreecoverfrom2020to2070fortheaverage,maximum,andminimumscenarios.AveragescenarioMaximumscenarioMinimumscenarioHM-wetHL-hotHH-middleCountyChange(percent)CountyChange(percent)CountyChange(percent)ProjectedincreasesTunica,MS+6.3Desha,AR+8.4Tunica,MS+5.8Quitman,MS+6.0Tunica,MS+7.3Quitman,MS+5.5Desha,AR+5.7Arkansas,AR+7.2Jefferson,WV+5.3Dyer,TN+5.7Monroe,AR+6.9Dyer,TN+5.2Cross,AR+5.2Cross,AR+6.8Boone,AR+4.8ProjecteddecreasesPetersburgcity,VA-7.6Petersburgcity,VA-7.9Danvillecity,VA-8.6Danvillecity,VA-8.6Newton,TX-9.4Emporiacity,VA-11.1Danvillecity,VA-8.8Emporiacity,VA-10.8Franklincity,VA-12.0Franklincity,VA-11.6BuenaVistacity,VA-12.4Emporiacity,VA-11.0BuenaVistacity,VA-12.1Franklincity,VA-12.0BuenaVistacity,VA-12.3HM=highwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HH=highwarming-highU.S.growth.4-24FutureofAmerica’sForestsandRangelandswereinGeorgia(-1.3percent),Maine(-1.1percent),anddecreasesinprojectedtreecover(table4-14).ThegrasslandVirginia(-1.1percent).TheNorth(+0.15percent)and(+0.44percent)anddesert(+0.21percent)ecoregionshadRockyMountain(+0.14percent)RegionsexhibitedoverallprojectedincreasesintreecoverwhiletheforestecoregionincreasesinprojectedtreecoverwhilethePacificCoast(-0.30percent)exhibitedprojecteddecreasesintreecover(-0.3percent)andSouth(-0.24percent)Regionsexhibited(table4-15).Table4-14.Treecoverin2020byRPAregion(percentoftotalarea)andprojectedchangesintreecoverin2070fortheaverage,maximum,andminimumscenarios.2070forscenario:Changeforscenario:RPAregion2020AverageMaximumMinimumAverageMaximumMinimumNorthHM-wetHL-hotHH-middleHM-wetHL-hotHH-middleSouthRockyMountain%%%%%%%PacificCoastConterminousU.S.39.739.939.939.80.150.170.1045.945.746.045.5-0.240.05-0.4117.918.018.018.00.140.130.1434.033.934.033.9-0.03-0.02-0.0332.732.732.832.60.020.10-0.04HM=highwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HH=highwarming-highU.S.growth.Table4-15.Treecoverin2020byecoregion(percentoftotalarea)andprojectedchangesintreecoverin2070fortheaverage,maximum,andminimumscenarios.Ecoregionsaresortedbydecreasingpercentchangefortheaveragescenario.2070forscenario:Changeforscenario:Ecoregion2020AverageMaximumMinimumAverageMaximumMinimumGrasslandHM-wetHL-hotHH-middleHM-wetHL-hotHH-middleDesertForest%%%%%%%ConterminousU.S.15.115.515.615.50.440.470.4215.015.215.215.20.210.190.2349.048.748.948.6-0.30-0.14-0.4032.732.732.832.60.020.10-0.04HM=highwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HH=highwarming-highU.S.growth.2020ResourcesPlanningActAssessment4-25ProjectedImperviousCoverChangethelargestprojectedincreasesinimperviouscoverwereDelaware(+1.9percent),California(+1.2percent),andNewWhiletheaveragetreecanopycoverdidnotchangemuch,Jersey(+1.0percent).ThePacificCoastRegionexhibitedwithsomeareasgainingtreecoverandotherareaslosingthelargestoverallincreaseinprojectedimperviouscovertreecover,imperviouscoverwasprojectedtoincrease(+0.87percent),followedbytheSouth(+0.62percent),throughoutmostoftheconterminousUnitedStatesfromNorth(+0.50percent),andRockyMountain(+0.18percent)2020to2070(figure4-21).TheoverallprojectedincreaseinRegions(table4-17).Theforestecoregionhadthelargestimperviouscoverintheaveragescenariowas0.46percent,projectedincreaseinimperviouscover(+0.61percent),23timesgreaterthanthenetpercentincreaseintreecoverfollowedbythegrassland(+0.30percent)anddesert(+0.26(0.02percent).Areasthatexhibitedthegreatestprojectedpercent)ecoregions(table4-18).increasesinimperviouscoverwereinthemoredenselypopulatedregionsoftheUnitedStates.DiscussionCountiesthathadthelargestprojectedincreasesofTheprojectionsoftreeandimperviouscoveracrosstheimperviouscoverwereinCaliforniaandVirginia(tableconterminousUnitedStatesweregenerallyconsistent4-16).Lessthan1percentofcountieswereprojectedtohaveamongtheaverage,maximum,andminimumscenarios.adecreaseinimperviouscoverandtheaveragedecreaseAllscenariosshowedanincreaseinimperviouscoverandwasnegligibleinthosecounties.Overall,theStateswithTable4-16.TopfivecountiesintheconterminousUnitedStatesintermsofgreatestprojectedincreasesanddecreasesinimperviouscoverfrom2020to2070fortheaverage,maximum,andminimumscenarios.AveragescenarioMaximumscenarioMinimumscenarioHM-wetHL-hotHH-middleCountyChange(percent)CountyChange(percent)CountyChange(percent)ProjectedincreasesSantaClara,CA+14.2SantaClara,CA+10.6Stanislaus,CA+19.7Stanislaus,CA+13.8SantaClara,CA+18.7Franklincity,VA+9.9Franklincity,VA+10.2Franklincity,VA+9.6BuenaVistacity,VA+9.1Bowie,TX+9.2Emporiacity,VA+8.1Stanislaus,CA+9.1BuenaVistacity,VA+8.7BuenaVistacity,VA+9.0Emporiacity,VA+8.2ProjecteddecreasesDaniels,MT-0.0015JudithBasin,MT-0.0015Daniels,MT-0.0015Hall,TX-0.0022Greeley,NE-0.0018Sheridan,KS-0.0023Greeley,NE-0.0023Hall,TX-0.0019Greeley,NE-0.0024Sheridan,KS-0.0023Floyd,IA-0.0051Sheridan,KS-0.0024Floyd,IA-0.0046Hall,TX-0.0032Floyd,IA-0.0051HM=highwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HH=highwarming-highU.S.growth.Table4-17.Imperviouscoverin2020byRPAregion(percentoftotalarea)andprojectedchangesinimperviouscoverin2070fortheaverage,maximum,andminimumscenarios.2070forscenario:Changeforscenario:RPAregion2020AverageMaximumMinimumAverageMaximumMinimumHM-wetHL-hotHH-middleNorthHM-wetHL-hotHH-middleSouth%RockyMountain%%%%0.50%%PacificCoast0.62ConterminousU.S.2.22.72.62.70.180.410.520.871.82.42.32.40.460.520.670.50.60.60.70.150.201.62.52.32.80.691.161.41.81.71.90.370.51HM=highwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HH=highwarming-highU.S.growth.4-26FutureofAmerica’sForestsandRangelandsFigure4-21.ImperviouscoverchangeforthreeRPAscenariosfrom2020alittlenetgrowthintreecovernationally.Thescenariosto2070.alsoexhibitedgenerallyconsistentregionalvariationofchangesintreeandimperviouscover.ImperviouscoverwasAverage(HM-wet)scenarioprojectedtoincreasebyanaverageof0.46percent(from1.4to1.8percentofthelandbase),whichisa34percentMaximum(HL-hot)scenariorelativeincreaseinimperviouscover.TheprojectedincreaseinimperviouscoverwasconsistentwithrecenttrendsMinimum(HH-middle)scenarioofincreasingimperviouscoverinurbanareasnationally(NowakandGreenfield2018)andwithinurbanareasglobally(NowakandGreenfield2020).Whileitislikelythatimperviouscoverwillincreaseduetoexpandinghumanpopulationsandassociatedlanddevelopment,theoutcomefortreecoverislesscertainbecausemanyinteractingfactorsaffecttreecover,includinglandusechange,climatechange,forestpoliciesandmanagementactivities,andnaturaldisturbances.Furthermore,thesefactorsarethemselvesinfluencedbythenaturalenvironmentandhumanpoliciesandactivities.Thus,theprojectedchangesintreecoverbasedonprojectedlandusechangesmaynotberealized,dependingonhowthosefactorsaltertreecover.Whiletotaltreecoverareaisnotprojectedtochangemuch,itislikelytoshiftamongregions,withsomeareasgainingandotherslosingtreecover.Byunderstandingthesepotentialchangesandthereasonsforthesechanges,forestmanagementplanscanbedevisedtosustainhealthyforeststhatpromotehumanhealthandwell-beingforcurrentandfuturegenerations.Table4-18.Imperviouscoverin2020byecoregion(percentoftotalarea)andprojectedchangesinimperviouscoverin2070fortheaverage,maximum,andminimumscenarios.Ecoregionsaresortedbydecreasingpercentchangefortheaveragescenario.Ecoregion2020Average2070forscenario:MinimumAverageChangeforscenario:MinimumHM-wetMaximumHH-middleHM-wetMaximumHH-middle%HL-hotHL-hot%%%%%%Grassland1.82.42.32.50.610.510.691.31.21.30.300.240.32Desert1.00.80.80.90.260.200.311.81.71.90.460.370.51Forest0.6ConterminousU.S.1.4HM=highwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HH=highwarming-highU.S.growth.2020ResourcesPlanningActAssessment4-27ProjectedLandUsePatternswereincludedinthelandscapepatternanalysis.Thissectionfocusesoncumulativesimulatedchangesfrom2020to2070❖Futurechangestospatialpatternsoflanduse,toevaluateclimatic,socioeconomic,andregionaldifferencesinfuturelandscapepatterns.suchaslandscapedominanceandnaturalinterfacearea,arestronglyrelatedtoprojectedThefuturelandscapepatternaroundeachpixelwaschangesingenerallandusearea.describedbyoneoffourdominanceclassesandoneoffourinterfaceclasses(seethesectionHistoricalForest❖NewdevelopmentisprojectedtooccurnearFragmentationandLandscapeContext)withina162-acreneighborhood.Inaddition,futureforestfragmentationwasexistingdevelopment,almostdoublingtheareaofassessedbyclassifyingfutureforestpixelsinto“interior”developed-dominantland.and“non-interior”forest,whereinteriorforestisdefinedasaforestpixelatthecenterofa162-acreneighborhood❖Projectednewdevelopmentincreasestheareathatisatleast90-percentforested(RiittersandRobertson2021).Despiteusingthesamegeneralmethods,wedonotofthedeveloped-naturalinterfaceandshiftslandrecommendstrictcomparisonsoflandscapepatternsinthisfromtheagricultural-naturalinterfacetothejointsectionandinthesectionHistoricalForestFragmentationdeveloped-agricultural-naturalinterface.andLandscapeContextduetoscaledifferencesandqualitativedifferencesbetweenlanduseandlandcover.❖ProjectedlandusepatternchangesareThecounty-levellanduseprojectionsforallscenariosconsistentacrossall20RPAscenario-climateindicateincreasesindevelopedlandarea,drawingprimarilyfutures.TheRPAscenarioshadagreaterimpactfromforestedandothernaturallands.Thefuturechangesthantheclimateprojectionsonfuturelandscapesoflandscapepatternsreflectthosetrends,asmodifiedbynearman-madelanduses,butbothdrivershadseveralsimulateddegreesofrandomnesswhichplacedaboutthesamedegreeofimpactinless-modifiedfuturelandusechangeseithernearorfarfromexistingarealandscapes.ofthesamelanduse(Brooksetal.2020).Drivenbythelanduseprojections,weexpectoverallincreasesintheareaof❖Whileoverallforestlanduseareawasprojecteddeveloped-dominatedlandscapesanddevelopedinterfaces,andadecreaseofinteriorforestarea.Whereforestandtodecrease,theshareofmore-contiguousforestagriculturelandusesarebothconvertedtodevelopedarea,wasprojectedtoincreaseintheRPASouththelandscapesbecomemoreheterogeneouswiththelocalCentral,Northeast,andNorthCentralSubregions.blendingofdeveloped,agriculture,andnaturalland.FuturelandusechangesarelikelytoresultinlandscapeWesummarizetheoverallresultsfortheconterminouspatternchanges,butadditionalanalyseswereneededtoUnitedStatesacrossallsimulations,followedbyprojectchangesinlandscapepatternsfromthecounty-comparisonsamongsubsetsofsimulationsdefinedbyRPAlevellanduseprojectionsdescribedinthesectionLandscenariosandclimateprojections(seethesidebarRPAUseProjections.Inthissection,thecounty-levellandScenarios).OneRPAscenarioandoneclimateprojectionuseprojectionsweredownscaled(disaggregated)intowereselectedas“basecases”andtheremainingmodelsspatiallyexplicitlandusemapsat90mspatialresolutionandscenarioswerecomparedintermsofdeviationsfrom(approximately2acresperpixel),andthefuturelandscapethebasecases.Thebasecases,chosentoreflect“middle-patternsweremeasuredonthosemaps.Thedownscalingground”situations,weretheHMRPAscenarioandtheappliedademand-allocationsimulationmethod(Brooksetmiddleclimateprojection.Allcomparisonsweremadeusingal.2020)toa2020landusebasemapfortheconterminousmedianoutcomesacrossallsimulationswithinagivensetUnitedStates.Foreachofthe20RPAscenario-climateofscenariosand/orclimateprojections.Projectedchangesfutures(fourRPAscenarios,fiveclimateprojections),amongclassesweresummarizedintermsofnetchanges.futurelandusemapsweresimulatedatdecadalintervalsuntil2070.Thesimulationswererepeated20timesforeachNationalResultsscenario-climatefuture,eachtimeassumingadifferentdegreeofspatialrandomnessoflandusechanges(BrooksAcrossallRPAscenarios,climateprojections,andetal.2020).Wethenmeasuredlandscapepatternsoneachsimulations,theprojectedtrendsinlandscapedominanceofthe2,000simulatedfuturemaps(20scenario-climategenerallyfollowedthecorrespondingcounty-leveltrends.futuresx5decadesx20simulations).FollowingthenamingDeveloped-dominatedlandareawasprojectedtoincreaseconventionsofthelanduseprojections,“developed”byamedianof47.3millionacres(95percent)from2020includestheNRIdevelopedclass,“agriculture”includestheto2070(table4-19).Thisareawasbalancedprimarilycropandpastureclasses,and“natural”includesforestandothernon-developedandnon-agriculturalNRIclasses.Thesimulatedspatialchangeswereappliedonlyonprivatelyownedlandarea(ConservationBiologyInstitute2016),butforconsistencywithoveralllandareatotals,thepublicland(Federal,State,andlocalgovernment)andTribalownerships4-28FutureofAmerica’sForestsandRangelandsTable4-19.Projectedchangesinlandscapedominancefrom2020to2070Figure4-22.ProjectednetareachangesoffourlandscapedominanceacrossallRPAscenarios,climateprojections,andsimulations.NotethattheclassesacrosstheconterminousUnitedStatesfrom2020to2070.Thebarsmedianvaluesdonotnecessarilysumtozero.representthemedianvaluesacrossallRPAscenarios,climateprojections,andsimulations.Theviolinplotsindicatethedistributionofsimulatedvalues,DominanceclassMedianchangeRangeofchangeRelativewiththeviolinheightrepresentingthefullrangeofvaluesandthewidthmedianrepresentingtheirrelativefrequency.DevelopedmillionacresmillionacreschangeNetchange(millionacres)Agriculture+47.3(+32.6,+56.8)60Natural-29.4(-35.0,-25.4)percentMixed-19.0(-24.3,-9.6)+95.140-0.03-7.03(-3.2,+9.6)-1.4920-0.02bymediandecreasesof29.4millionacres(7percent)of0agriculture-dominatedlandandby19.0millionacres(1-20percent)ofnatural-dominatedland.Thelandareainthe“mixed”dominanceclass(wherenoonelandusecoversDevelopedAgricultureNaturalMixedmorethan60percentofthesurroundingarea)wasprojectedtoincreaseslightlyacrossallmodelsandscenarios(<0.1DominanceClassmillionacres,<0.1percent).Figure4-22illustratesthedistributionofsimulatedchangesforallsimulationsoftheFigure4-23.ProjectednetareachangesoffourlandscapeinterfaceclassesRPAscenario-climatefutures.acrosstheconterminousUnitedStatesfrom2020to2070.ThebarsrepresentthemedianvaluesacrossallRPAscenarios,climateprojections,andWithoneexception,theprojectedRPAregionaltrendsinsimulations.Theviolinplotsindicatethedistributionofsimulatedvalues,withdominanceclassarea(table4-20)generallyconformedtotheviolinheightrepresentingthefullrangeofvaluesandthewidthrepresentinghistoricaltrendsinlandcoverdominance(figure4-13).Thetheirrelativefrequency.exceptionwasthatthehistoricalincreaseinagriculture-dominatedlandfrom2001to2016intheRockyMountain75Regionwasnotprojectedtocontinue.Whiledifferencesbetweenlandcoverandusemayaccountforsomeofthis50trajectorychangeinlandscapedominance,theprojectionswereconsistentwiththecounty-levellanduseprojectionNetchange(millionacres)25models,whichindicatedafuturedecreaseofagriculturelandareainthatregion.0Wealsoassessedprojectedtrendsinthemedianareas-25ofinterfaceclasses(figure4-23,table4-21).Acrossallsimulations,themedianshareinthedevelopedinterface-50classwasprojectedtoincreaseby49.9millionacres(76percent)from2020to2070,comparabletotheprojectedDevelopedAgricultureNeitherBothincreaseofareaindeveloped-dominatedland.Likedominance,thisincreasewasdrawnfromtheagricultureinterfaceareawhichhadaprojecteddecreaseof45.6InterfaceClassTable4-20.Projectedmedianchangeinlandscapedominanceareafrom2020to2070acrossallRPAscenarios,climateprojections,andsimulations,byRPAregion.Valuesinparenthesesindicatetherange.Landscapedominanceclass(millionacres)RPAregionDevelopedAgricultureNaturalMixedNorth+12.4(8.69,14.7)-0.66(-1.29,+2.14)South+21.5(16.1,26.0)-11.4(-12.9,-9.72)-0.74(-1.47,-0.09)-2.51(-3.89,-1.99)RockyMountain+5.89(2.99,7.60)+1.82(0.94,3.22)PacificCoast+7.51(4.89,9.37)-10.7(-14.3,8.63)-8.97(-11.2,-4.72)+1.33(0.952,2.29)-4.25(-4.85,-3.68)-3.48(-5.04,-0.76)-3.05(-3.87,-2.41)-5.76(-7.36,-3.89)2020ResourcesPlanningActAssessment4-29Table4-21.Projectedchangesininterfaceclassareafrom2020to2070Figure4-24.DistributionofprojectedchangesininteriorforestareafromacrossallRPAscenarios,climateprojections,andsimulations.Notethatthe2020to2070,acrossallRPAscenarios,climateprojections,andsimulations.medianvaluesdonotnecessarilysumtozero.Theviolinheightrepresentsthefullrangeofvalues,andthewidthrepresentstheirrelativefrequency.RelativemedianInterfaceclassMedianchangeRangeofchangechangepercentDevelopedmillionacresmillionacres+76.1Agriculture+49.9(+39.1,+69.2)-8.04Neither-45.6(-52.6,-38.7)-1.69Both-18.2(-40.5,-5.05)+19.6+15.0(+11.0,+25.2)millionacres(8percent),andnon-interfaceareawhichwasClimateProjectionResultsprojectedtodecreaseby18.2millionacres(2percent).The“both”interfacearea(wherebothdevelopedandagricultureTocomparethemaineffectsofthedifferentclimateinterfacewithnaturallandscapes)wasprojectedtoincreaseprojectionsonprojectedlandscapepatterns,weaggregatedby15.0millionacres(20percent),whichcontrastswiththeprojectedchangesacrossallRPAscenariosandsimulationsrelativelystableshareoflandinthecorrespondingmixedseparatelywithineachclimateprojectionandcomparedthedominanceclass.Thisdifferenceisaccountedforbynotingmedianresultsofeachprojectionwiththoseofthemiddlethattheprojecteddecreaseinagricultureinterfaceareaclimateprojectionbasecase.Figure4-25showstheeffectsexceedsthatoftheagriculture-dominatedareabymoreofthedifferentclimateprojectiononprojectedfuturethan15millionacres.Putanotherway,whilelandswithlandscapedominancepatterns.Impactsoneachdominanceagriculturalcontextaregenerallybeingconvertedtolandsclasswereconsistentacrossallclimateprojections;however,withamoredevelopedcontext,aconsiderablepartofthisconversion(the15millionacres)isfromnon-interfacelandFigure4-25.Theeffectofclimateprojectiononlandscapedominance,withmorethan90-percentagricultureintheneighborhooddisplayedasmedianprojectedchangefrom2020to2070.tolandthathasatleast60-percentagriculture(i.e.,remainsagriculture-dominant)butnowincludesatleast10-percentDominanceClassdevelopedlandaswell(i.e.,becomes“both”interface).Whilethevaluesreportedherearenetchangesacrossallsimulations,mapsofgrosschange(notshownhere)suggestthatconversionofnaturallandtoagriculturelandoccursnearexistingdevelopment,andthatnewdevelopedlandtendstobeconnectedtoexistingdevelopment.Supportforthisinterpretationisinthe“longtails”intheviolinplots(figure4-23),wheresimulationswithextremelylargeareasofdevelopedinterfacehavecorrespondinglysmallareasofnon-interfaceland.Weassessedprojectedtrendsofinteriorforestareatoevaluatetheeffectsoflandusechangeonforestfragmentationfrom2020to2070.Overallsimulations,themedianprojectedinteriorforestareachangewasadecreaseof1.5millionacres(figure4-24).Thatlossisequivalenttoapproximately12percentoftheprojectednetforestarealossduringthattime(table4-9).However,variationacrosstheRPAscenariosandclimateprojectionswassuchthatoveraquarterofthesimulationsexhibitedaprojectedincreaseininteriorforest,suggestingthatthedirectionandthedegreeofinteriorareachangedependsonbothfutureclimateandsocioeconomictrends.Climateprojectionleastwarmhotdrywetmiddle4-30FutureofAmerica’sForestsandRangelandsthehotprojectionproducedthemostdivergentresults.InFigure4-27.Theeffectofclimateprojectiononinteriorforest,displayedasparticular,thehotprojectioninhibitedthegeneralincreasemedianprojectedchangefrom2020to2070.indeveloped-dominatedlandarea(4.3millionfeweracresgainedthanthemiddleprojectionof47.3millionacresClimateprojectionleastwarmhotdrywetmiddlegained),withacorrespondinginhibitioninthereductionofnatural-dominatedland(5.8millionfeweracreslostby2.2millionacresbeyondthemiddleprojection,withthethanthemiddleprojectionof19.5millionacreslost).balancespreadacrosstheotherinterfaceclasses.ThedifferencebetweenthehotandleastwarmclimateprojectionswaslargerthanthedifferencebetweenthedryFigure4-27showstheeffectofthedifferentclimateandwetprojection.Thewetprojectionresultedinthelargestprojectionsonprojectedfutureinteriorforestarea.Aswithaccelerationtoreductionstoagriculture-dominatedland(1.8dominanceandinterfaceclasses,thehotclimateprojectionmillionacresmorelostthanthemiddleprojectionof28.5producedthemostdivergentresults,yieldinginthiscaseamillionacreslost),withthebalancespreadacrossdevelopedmedianprojectedincreasetointeriorforestarea.Thisresultandnaturaldominantlands.contrastswithadecreaseof1.8millionacresprojectedbythemiddleclimateprojection,aswellasdecreasesof1.5Figure4-26showstheeffectsofthedifferentclimatemillionacresunderthedryandwetprojections,and1.9projectionsonfutureinterfaceclasses.Aswithlandscapemillionacresundertheleastwarmprojection.Underthehotdominance,allclimateprojectionsresultinthesameprojection,therelativelyslowerincreaseofdevelopedlanddirectionofchange:increasingdevelopedinterfaceandresultsinrelativelymoreremainingnaturalland,includinginterfacebetweenbothdevelopedandagriculturewiththeinteriorforest.Thissuggeststhatunderthehotprojection,naturallandscape(“both”),withdecreasingagricultureanddevelopedlandisdrawingfromamixtureofnon-interiorneither-interface.Thehotclimateprojectionagaingenerallyforestandagriculturallands.projectsthemostdivergentresults,includinganinhibitedincreasetodevelopedinterfacelandandacorrespondingRPAScenarioResultsinhibiteddecreasetotheneitherinterface.Alsosimilartotheireffectsonlandscapedominance,thedifferencebetweenTocomparetheeffectsofthedifferentRPAscenariosonthehotandleastwarmclimateprojectionswaslargerthanprojectedlandscapepatternsfortheconterminousUnitedthedifferencebetweenthedryandwetprojections.ThehotStates,weaggregatedprojectedchangesacrossallclimateprojectionreducedtheprojecteddevelopedinterfacenetgainprojectionsandsimulationsseparatelywithineachRPAby3.2millionacres,consistentwiththeeffectondeveloped-scenario(figure4-14),andthencontrastedthemedianresultsdominatedland.Thewetprojectionresultedinthemostforeachscenariowiththebasecase(HMRPAscenario).accelerateddecreaseinagricultureinterfaceland(similartothatprojection’seffectonagriculturedominatedland):Figure4-28showstheeffectoftheRPAscenarioonprojectedagricultureinterfaceclassareawasprojectedtodecreaselandscapedominance.Thedifferencesbetweenhighandlowgrowth(HHandHL,respectively)hadagreatereffectonFigure4-26.Theeffectofclimateprojectiononnaturalinterface,displayedaslandscapedominancethanthecontrastbetweenlowerandmedianprojectedchangefrom2020to2070.highatmosphericwarming(LMandHM,respectively).Highgrowthwasprojectedtoincreasedeveloped-dominatedlandInterfaceClassby9.3millionacresmorethanthelowgrowthscenarioand6.4millionacresabovetheHMbasescenario.ThisadditionalClimateprojectionleastwarmhotdrywetmiddle2020ResourcesPlanningActAssessment4-31Figure4-28.TheeffectofRPAscenarioonlandscapedominance,displayedFigure4-29.TheeffectofRPAscenarioonnaturalinterface,displayedasasmedianprojectedchangefrom2020to2070.medianprojectedchangefrom2020to2070.DominanceClassInterfaceClassRPAScenarioLMHLHMHHRPAScenarioLMHLHMHHLM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highLM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.warming-moderateU.S.growth;HH=highwarming-highU.S.growth.developmentcamefromagriculturalandnaturallands,resulting(comparefigures4-25and4-28)andlandscapeinterfaceinlowerprojectedareasforthosedominanceclasses.The(comparefigures4-26and4-29)nearartificiallycreatedlandreducedprojecteddeveloped-dominantlandprojectedundertheuses.Incontrast,bothdriversofchangeresultedinaboutthelowgrowthscenarioresultsinmoreagricultural-andnatural-samedegreeofvariationinless-modifiedlandscapes.Takingdominantareas.TrendsfortheLMscenariotendedtomirrorlandscapedominanceasanexample,therangeofdeveloped-thosefortheHHscenario,albeitwithareducedmagnitudeofdominatedlandareain2070is9.2millionacresacrossRPAchangerelativetotheHMbasescenario.scenariosand5.9millionacresacrossclimateprojections.Foragriculture-dominatedlandarea,therangeis3.7millionFigure4-29showstheeffectoftheRPAscenarioonprojectedacresacrossRPAscenariosand1.8millionacresacrossinterfaceclassarea.Generalpatternsconformedtothoseclimateprojections.Therangefornatural-dominatedlandforlandscapedominance,withthemaindifferencebeingareadifferedverylittlebetweenRPAscenarios(6.3millionanincreasedshiftfromtheagricultureinterfaceintotheacres)andclimateprojections(6.2millionacres).Whilethe“both”interfaceclassascomparedtoagriculture-andmixed-dominatedland,respectively.ThiseffectwasmorepronouncedFigure4-30.TheeffectofRPAscenariooninteriorforest,displayedasundertheHHscenario,suggestingthatthedriverofthemedianprojectedchangefrom2020to2070.increased“both”interfaceareaovertheagricultureinterfaceiseconomicgrowth(withmoregrowthleadingtomoreinterfaceRPAScenarioLMHLHMHHareacontainingbothdevelopedandagricultureland).LM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highFigure4-30showstheeffectoftheRPAscenarioonwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.projectedinteriorforestarea.WhilethelossofinteriorforestareaunderHLislessthaninotherscenarios,themedianinteriorforestareaisprojectedtodecreaseacrossallscenarios.Thelossofinteriorforestareafrom2020to2070undertheHHscenario,2.6millionacres,isoverfourtimesgreaterthanthelossundertheHLscenario(0.6millionacres).Aswithlandscapedominanceandinterfaceclasses,comparingprojectedresultsassociatedwiththedifferenteconomicgrowthlevels(SSP)ofthescenariosresultedinlargerdifferencesthanthedifferentwarminglevels(RCP).ComparingtherelativesensitivityoftheresultstoRPAscenariosandclimateprojections,wefoundtheformertobeastrongerdriverofdifferencesinlandscapedominance4-32FutureofAmerica’sForestsandRangelandsoppositeresultwasobtainedforthemixeddominanceclass,LandscapeContext),withtheexceptionthatthehistoricalthemagnitudesofthoserangesaresmallincomparisonincreaseofagriculture-dominatedareaintheRockytotheotherdominanceclasses(0.4millionacresforRPAMountainRegionwasnotprojectedtocontinue.scenariosversus0.9millionacresforclimateprojections).Likenatural-dominatedlandarea,thereisslightlymoreProjectedtrendsofinterfaceclassareasweregenerallyvariationamongclimateprojectionsthanamongRPAsimilartothoseoflandscapedominance,exceptforthescenariosfornon-interfacelandareaandinteriorforest“both”interfaceclassascomparedtomixed-dominatedclassareabecausethoseconditionsgenerallyoccurinless-(figure4-32):themedian“both”interfaceareaincreasedformodifiedlandscapes.allsubregions,whereastheNortheast,Southeast,andSouthCentralSubregionsallsawdecreasestomixed-dominatedRegionalResultslandarea.Forchangesinbothdominanceandinterfaceclasses,subregionaldifferencesininitialconditions(i.e.,theProjectedchangeswereexpectedtovarygeographicallyoriginalareaofeachclass)largelyexplainedsubregionalbecauseofregionaldifferencesinbiophysicalconstraintsdifferencesofthechange(analysisnotshownhere).Theonlanduseandininitialsocioeconomicconditions.Thoseprojectedchangesininterfaceclassesweregenerallysimilardifferencesimplythatregionaldifferencesareinseparabletohistoricalchangesbasedonlandcover,withthesamefromclimateprojectionandRPAscenariodifferences,whichexceptiontohistoricaltrendsintheRockyMountainRegion.preventsidentifyingprojectionorscenariodifferencesattheregionallevel.Thus,weestimatedregionalchangesinFigure4-32.Projectednetareachangeoffourlandscapeinterfaceclassestermsofmedianoutcomesacrossallsimulations,byRPAfrom2020to2070,byRPAsubregion.Thebarsrepresentmediansubregionalsubregion(figure2-1).netchangesacrossallRPAscenarios,climateprojections,andsimulations.Theareaofdeveloped-dominatedlandwasprojectedtoInterfaceClassincreaseinallsubregions,buttheoffsettingchangestootherdominanceclassesvariedamongsubregions(figure4-31).RPAsubregionNortheastSoutheastGreatPlainsPacificNorthwestAgriculture-dominatedareawasprojectedtodecreaseinallNorthCentralSouthCentralIntermountainPacificSouthwestsubregions,whilenatural-dominatedlandareawasprojectedtodecreaseinallsubregionsexcepttheNorthCentralandGreatPlainsSubregions.Theareaofthemixeddominanceclassisprojectedtodecreaseintheeasternsubregionsandincreaseinthewesternsubregions.Theprojectionsaregenerallysimilartohistoricallandcoverdominanceresults(seethesectionHistoricalForestFragmentationandFigure4-31.Projectednetareachangeoffourlandscapedominanceclassesfrom2020to2070,byRPAsubregion.ThebarsrepresentmediansubregionalnetchangesacrossallRPAscenarios,climateprojections,andsimulations.DominanceClassProjectedchangesofinteriorforestareaweredrivenbythenetlossoftotalforestareaandbythelocationsofforestRPAsubregionNortheastSoutheastGreatPlainsPacificNorthwestgainsandlossesinrelationtothelocationsoftheextantNorthCentralSouthCentralIntermountainPacificSouthwestforest.Despitetheoverallprojectedlossoftotalforestarea,theprojectednetchangeininteriorforestfrom2020to2070variedbysubregion(figure4-33).TheSoutheastSubregionandthewesternsubregionswereprojectedtoexperienceadecreaseofinteriorforestarea,withthelargestareadecreaseinthePacificNorthwestSubregion.Interiorforestareawasprojectedtoincreaseinthenorthernandeasternsubregions,particularlyintheSouthCentralandNorthCentralSubregions.Thatthesesubregionalincreaseswereprojecteddespiteconcordantoverallforestlosssuggestsaconsolidationofcontiguousforestinthosesubregions.2020ResourcesPlanningActAssessment4-33Figure4-33.Projectednetchangeofinteriorforestareafrom2020to2070,ChaptersbutwerenotexplicitlyincludedinourlandusebyRPAsubregion.ValuesshownarethemediansacrossallRPAscenarios,models.Placingadditionalvalueonthoseserviceswouldtendclimateprojections,andsimulations.toincreasetherelativeeconomicreturntoforestcomparedtootherlandusesthatdonotsupplythoseservices,whichinturn5.0wouldtendtoincreasetheareaofforestremainingforest.2.5OurcurrentmodelssuggestthatsocioeconomicdriversoflanduseandcoverchangeplayamoresignificantrolethanNetchange(millionacres)0.0climatedrivers.Ifso,thenmanagementactionstakenin-2.5responsetoactualorexpectedclimatechangeinaspecificcircumstanceareunlikelytoalterthefundamentaleconomic-5.0driversofforestlandusechange,unlesstheactualchangesaresounusualorwidespreadthateconomicconsiderationsRPAsubregionNortheastSoutheastGreatPlainsPacificNorthwestplayasmallerroleinfuturechoicesoflanduseandcover.NorthCentralSouthCentralIntermountainPacificSouthwestAtthesametime,climatechangehasthepotentialtobecomethemostimportantdriveroflong-termlandusechanges.WhilethesemedianprojectionsareimpactedbybothclimateOurfutureprojectionmodelsarebasedonhistoricallanduseandsocioeconomicfactors,aspreviouslyshownfortheandeconomicdatafromatimewhenclimatechangewasoverallconterminousUnitedStates,wefoundnoinstancearguablylessimportantthanitmaybecomeinthefuture.wheresuchvariationchangedthedirectionoftheprojectedEvenintensebutlocalizeddisturbancessuchhurricanessubregionaltrends.andlargewildfireshavenotfundamentallyalteredlanduse,northemajordriversoflandusechangeatregionalscales.ManagementImplicationsThisisnottosaythatclimatechangehadlessimportinpriordecades,onlythatourfutureprojectionsarebasedHistoricalpatternsoflanduseandlandcoverchangesondatafromthatperiod.Itisthereforenotsurprisingthatarelikelytocontinueunderanyfuturescenario,albeitateconomicfactorsdominateclimatefactorsinourfuturedifferentratesthanprojectedforthe2010RPAAssessment.projectionsofthenation’slandresources.However,intheApartfromtheprojectedincreaseinurbanlandusearea,pastseveralyearsthereisevidenceoflarge-scaleclimate-mostlyderivingfromlandinforestandagricultureuses,therelatedeventssuchasprolongedextremedroughtintheprimaryimplicationisrelatedtothespecificlocationsofnewWesternStateswhichcouldbeharbingersoffundamentalurbanordevelopedland.Willfutureurbangrowthcontinuechangesinthecapacitytosupportsomelandusesovertoexpandupontheexistingurbanareasasourprojectionslargeareas.Anotherexampleissealevelrise,whichhastheindicate?Orwillothersocioeconomicdriverssuchaspotentialtochangelandusedynamicsoverlargecoastalresourcescarcityorpandemicsleadtoaconcentrationregions.Withtheadventofsuchclimate-relatedphenomena,withinexistingurbanareasortoamoredispersedpatternofsomeareasmaynolongerhavethecapacitytosupportdevelopment?Urbandensificationwouldplaceadditionaltraditionallandusesindefinitely,whichcouldshiftthosepressuresonurbanforests,whiletheconversionofrurallandusesandtheassociatedprovisionofecologicalserviceslandwouldcreatenew“urbaninterface”landscapestoothergeographicareas.Whileitmayneverbepossibletowherelandmanagers,bothprivateandpublic,couldfaceadequatelyprojectallthelocalchangesinclimate,landuse,novelpressuresinsomeareas.Asmorestakeholderswithandlandcoverthatcouldoccur,modelimprovementswouldpotentiallynewexpectationsenterconversationsaboutlandhelptobetteraddresstherangeofpotentialfutureimpactsmanagement,moreemphasiscouldbeplacedon“all-lands”onthelandbaseatbothlocalandregionalscales.or“partnership”managementapproachesthatencouragepublicengagement.ConclusionsOuranalysesoflandusechangeconsideredonlythevalueofThischaptersummarizedrecenttrendsoflanduseandlandtimbercommoditiesinvaluingforestlandanddidnotdirectlycoverandpresentedfutureprojectionsto2070basedonvalueotherforestecosystemservicessuchascarbonstorage,RPAscenarios.HistoricalanalysisofFIAdataindicatedwaterquantity,orwildlifehabitat.ThesevaluesarediscussedthatthetotalforestandwoodlandareaintheconterminousintheForestResources,WaterResources,andBiodiversityUnitedStateshasbeenrelativelystableforseveraldecades.TheNRIdataforonlynon-Federalforestlandindicatedaslightgainofforestareafrom1982to2012,mostlyfrompreviouslyagriculturallanduses.Incontrast,thetotalareawithforestcover,acrossalllanduses,declinedbyapproximately3percentfrom2001to2016.Thedifference4-34FutureofAmerica’sForestsandRangelandswasexplainedinpartbythelossofforestcoverinareasnotCoulston,J.W.;Reams,G.A.;Wear,D.N.;Brewer,C.K.2014.Anusedasforest,andinpartbythetemporarylossofforestanalysisofforestlanduse,forestlandcoverandchangeatpolicy-coverinareasusedasforest.relevantscales.Forestry.87(2):267–276.https://doi.org/10.1093/forestry/cpt056.Whilethetotalforestareahasbeenrelativelystable,theforestandlandresourcesoftheUnitedStatesareCoulston,J.W.;Wear,D.N.;Vose,J.M.2015.Complexforestdynamicshighlydynamicovertimeandspace.Becausethespatialindicatepotentialforslowingcarbonaccumulation.ScientificReports.5:arrangementoftheforestchangesovertime,theconsequent8002.https://doi.org/10.1038/srep08002.changesinfragmentationandlandscapecontextareoftenmuchlargerthansuggestedbynetareachangealone.Curtis,P.G.;Slay,C.M.;Harris,N.L.;Tyukavina,A.;Hansen,M.C.Shortertermchangessuchastheuseofagricultureland2018.Ahigh-resolutionglobalmapenablesaclassificationofthemainforpastureorcultivatedcropsandthetransitionalcoverdriversofforestloss.Science.361:1108–1111.https://doi.org/10.1126/offorestlandusewithforest,grass,orshrubcoversarescience.aau3445.drivenlargelybyeconomicreturnstoagricultureandforestmanagementbutalsobytemporaryforestdisturbances.SuchDomke,G.M.;Walters,B.F.;Nowak,D.J.;Smith,J.E.;Ogle,S.M.;changesarepervasiveonprivatelyownedland,relativelyCoulston,J.W.;Wirth,T.C.2020a.Greenhousegasemissionsandlesscommononpubliclands,andcumulativelyaffectaremovalsfromforestland,woodlands,andurbantreesintheUnitedmuchlargertotalareathanisindicatedbynetareachangesStates,1990–2018.ResourceUpdateFS-227.Madison,WI:U.S.overtime.Overthelongterm,themostimportantlastingDepartmentofAgriculture,ForestService,NorthernResearchStation.5landusechangehasbeenandwilllikelycontinuetobep.https://doi.org/10.2737/FS-RU-227.theconversionofrurallandstourbanizedlands,drivenbyincreasingU.S.populationandrelativeeconomicreturnstoDomke,G.M.;Oswalt,S.N.;Walters,B.F.;Morin,R.S.2020b.developmentincomparisonwithreturnstoeitheragricultureTreeplantinghasthepotentialtoincreasecarbonsequestrationorforestoperations.capacityofforestsintheUnitedStates.ProceedingsoftheNationalAcademyofSciences.117(40):24649–24651.https://doi.org/10.1073/LiteratureCitedpnas.2010840117.Bar-Massada,A.;Radeloff,V.C.;Stewart,S.I.2014.BioticandabioticDudley,N.;Stolton,S.eds.2008.Definingprotectedareas:aneffectsofhumansettlementsinthewildland-urbaninterface.BioScience.internationalconferenceinAlmeria,Spain.Gland,Switzerland:64:429–437.InternationalUnionfortheConservationofNature.220pp.Bigelow,D.P.,Lewis,D.J.;Mihiar,C.2022.AmajorshiftinU.S.landEggleston,H.S.;BuendiaL.;Miwa,K.;Ngara,T.;Tanabe,K.,eds.2006.developmentavoidssignificantlossesinforestandagriculturalland.2006IPCCGuidelinesforNationalGreenhouseGasInventories.Japan:EnvironmentalResearchLetters.17(2):024007.InstituteforGlobalEnvironmentalStrategies.Bradbury,M.;Peterson,M.N.;Liu,J.2014.Long-termdynamicsofErvin,J.2003.Protectedareaassessmentsinperspective.BioScience.householdsizeandtheirenvironmentalimplications.Population&53:819–822.https://doi.org/10.1641/0006-3568(2003)053[0819:PAAIPEnvironment.36:73–84.]2.0.CO;2.Brooks,E.B.;Coulston,J.W.;Riitters,K.H.;Wear,D.N.2020.UsingaForman,R.T.T.;Alexander,L.E.1998.Roadsandtheirmajorecologicalhybriddemand-allocationalgorithmtoenabledistributionalanalysisofeffects.AnnualReviewofEcologyandSystematics.29:207–231.landusechangepatterns.PLOSONE.15(10):e0240097.https://doi.https://doi.org/10.1146/annurev.ecolsys.29.1.207.org/10.1371/journal.pone.0240097.Hansen,A.J.;Knight,R.L.;Marzluff,J.M.;Powell,S.;Brown,K.;Gude,Burrill,E.A.;Wilson,A.M.;Turner,J.A.;Pugh,S.A.;Menlove,J.;P.H.;Jones,K.2005.Effectsofexurbandevelopmentonbiodiversity:Christiansen,G.;Conkling,B.L.;David,W.2018.TheForestInventorypatterns,mechanisms,andresearchneeds.EcologicalApplications.15:andAnalysisDatabase:databasedescriptionanduserguideversion1893–1905.8.0forPhase2.U.S.DepartmentofAgriculture,ForestService.946p.https://www.fia.fs.usda.gov/library/database-documentation/.(13JulyHeisler,G.M.;Brazel,A.J.2010.Theurbanphysicalenvironment:2023)temperatureandurbanheatislands,in:Aitkenhead-Peterson,J.;Volder,A.e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S.DepartmentofWeynand,T.,eds.Inpress.UrbanandwildlandurbaninterfaceforestsAgriculture,ForestService,NaturalResourcesConservationService.andrangelandsinachangingenvironment.NewYork:Springer.Ames,IA:IowaStateUniversity,CenterforSurveyStatisticsandMethodology.http://www.nrcs.usda.gov/technical/nri/12summary.USDAForestService.2016.FutureofAmerica’sforestsandrangelands—updatetotheForestService2010ResourcesPlanningActAssessment.Gen.Tech.Rep.WO-94.Washington,DC:U.S.DepartmentofAgriculture,ForestService,WashingtonOffice.Authors:MarkD.Nelson,USDAForestService,NorthernResearchStationGrantM.Domke,USDAForestService,NorthernResearchStationKurtRiitters,USDAForestService,SouthernResearchStationMirandaH.Mockrin,USDAForestService,NorthernResearchStationJohnW.Coulston,USDAForestService,SouthernResearchStationDavidJ.Lewis,OregonStateUniversityChristopherMihiar,USDAForestService,SouthernResearchStationDavidJ.Nowak,USDAForestService,NorthernResearchEvanB.Brooks,VirginiaTechStation(emeritus)EricJ.Greenfield,USDAForestService,NorthernResearchStation2020ResourcesPlanningActAssessment4-37Chapter5DisturbancestoForestsandRangelandsCostanza,JenniferK.;Koch,FrankH.;Reeves,Matt;Potter,KevinM.;Schleeweis,Karen;Riitters,Kurt;Anderson,SarahM.;Brooks,EvanB.;Coulston,JohnW.;Joyce,LindaA.;Nepal,Prakash;Poulter,Benjamin;Prestemon,JeffreyP.;Varner,J.Morgan;Walker,DavidM.2023.DisturbancestoForestsandRangelands.In:U.S.DepartmentofAgriculture,ForestService.2023.FutureofAmerica’sForestandRangelands:ForestService2020ResourcesPlanningActAssessment.Gen.Tech.Rep.WO-102.Washington,DC:5-1–5-55.Chapter5.https://doi.org/10.2737/WO-GTR-102-Chap5.Disturbancesincludingfire,insectanddiseaseoutbreaks,whicharesummarizedforforestsandrangelands,withtheanddroughtareubiquitousinforestsandrangelands,exceptionsofinsectanddiseaseagentsandremovalswhichandmanydisturbanceeventsarepartsofthenaturaldynamicsaresummarizedonlyforforests.Attheendofthechapter,offorestandrangelandecosystems.ThischapterisanewwepresentalookatrecentexposureofforeststomultipleadditiontotheResourcesPlanningAct(RPA)Assessmentdisturbances:removal,stress,andfire.Quantitativesummariesandsummarizesdisturbancetrendsintherecentpastandemphasizeexposuretodisturbances:thatis,trendsorchangesinprojectedfuturetrendswithinforestsandrangelandsacrosstheextent,severity,frequency,ordurationofadisturbancefromtheconterminousUnitedStates.Weassessstatusandtrendsofhistoricalconditions,orexpectedfuturechangefromrecentabioticandbioticdisturbanceagents,includingfire,drought,trends(Glicketal.2011,Thorneetal.2018).Wherepossible,insectsanddisease,andnonnativeinvasiveplants.Alongwithweexaminedisturbanceexposurealongsideinformationaboutthoseagents,wesummarizesomeforestmanagementactions—thesensitivityandadaptivecapacityofforestsandrangelandsprescribedburningandremovals—thatcanbeclassifiedastodisturbancesandchangingdisturbanceregimes.Weconcludedisturbancesbecausetheyalterenvironmentalconditionsandwithgeneralmanagementconsiderationsforincorporatingleadtochangesinforeststructureorcommunitycompositioninformationonchangingdisturbanceregimesintoplanning(WhiteandJentsch2001),eventhoughtheycanleadtoforestandactionsthatcanincreaseresilienceofforestandrangelandresilienceinthelongterm.Thechapterisorganizedintoecosystemstoglobalchange.sectionsfocusedonindividualdisturbanceagents,mostofKeyFindings❖Theannualareaoffireinforestsandrangelandshasincreasedsince1984,andtheaverageannualareaburnedfrom2000to2017wasmorethandoublethepre-2000average.❖ThetwowesternRPAregionshavegenerallyhadhigherexposuretofireanddroughtthantheeasternregions,aswellasthegreatestratesoftreemortalitycausedbyinsectsanddiseases.Incontrast,forestsintheRPASouthRegionhaveexperiencedthehighestratesofremovals.❖Thehighestratesofinvasionbynonnativeplantsoccurnearagriculturalordevelopedlanduses,primarilyinforestsintheRPASouthRegionandportionsoftheNorthRegion,aswellasrangelandsinthePacificCoastRegion.❖Fire-causedtreemortalityinforestsisexpectedtoincreaseby2070.ThehighestratesoffiremortalityareexpectedifclimatefollowsthehotordryclimatefuturesunderanyofthehighwarmingRPAscenarios.❖Droughtexposureforforestsandrangelandsisexpectedtoincreaseby2070,andforestandrangelandecosystemsintheSouthwestareexpectedtoexperiencethemostsubstantialincreases.2020ResourcesPlanningActAssessment5-1AdisturbancecanbedefinedasaneventthatchangesFireinForestsandRangelandsenvironmentalconditionswithinanecosystem.Disturbancescombinewithotherbiotic,abiotic,andbiophysicalfactors❖Theannualareaoflargefireshasincreasedintoaffectforests,rangelands,andtheservicesandresourcesderivedfromthoseecosystems(Kellyetal.2020,Seidlbothforestsandrangelandsoverthe1984toetal.2016).Asclimate,otherbiophysicalfactors,and2017period.Theaverageannualareaburnedbymanagementregimeschange,disturbanceregimesarelargewildfiressince2000ismorethandoublethebeingaltered(Bowmanetal.2020,Donovanetal.2017,pre-2000average.Pureswaranetal.2018,Sommerfeldetal.2018),withthepossibilityofsomedisturbancetypesbecomingmore❖Inforests,prescribedfiresconductedforfrequent,severe,orlongerinduration(Cooketal.2015,Daleetal.2001,Seidletal.2017).Atthesametime,somemanagementhavebeenmostprevalentinthedisturbancetypeshavebecomelessfrequentincertainSouthRegion.ecosystems(forexample,NowackiandAbrams2014,Steeletal.2015).Thesealterationstodisturbanceregimeshave❖Increasesinthevolumeoftreeskilledbyfireinthepotentialtodrivechangesinthedistribution,structure,speciescomposition,orfunctionofforestandrangelandforestsareexpectedby2070,withthegreatestecosystems,puttingthoseecosystemsatriskandpresentingincreasesassociatedwiththehotanddryclimatechallengesformanagement(Anderson-Teixeiraetal.2013,futuresunderthehigherwarmingscenarios.Clarketal.2016,Coopetal.2020,Voseetal.2018).Thereismountingevidencethatmanagementactionssuchas❖Inforests,increasesintheannualareaofthinningorprescribedfiremayplaykeyrolesinmitigatingoramelioratingtheimpactsofdisturbanceslikedroughtmoderate-severityfiresareexpectedinallRPAinsomeecosystems(BradfordandBell2017,Knappetal.regionsby2070underallRPAscenarios.Inthe2021,Krofchecketal.2018,Voseetal.2019).IdentifyingPacificCoastandSouthRegions,theareaoftrendsin,andattributingcausesofdisturbancesonforestshigh-severityfiresisalsoexpectedtoincrease,andrangelandsenablesexaminationofeffectsonforestandwhileintheRockyMountainandNorthRegions,rangelandresourcesandcaninformregionalandnationaltheareaofhigh-severityfiresisprojectedtoeithermanagementandpolicy.Inthischapterwesummarizeincreaseordecrease,dependingonthewarmingtrendswithintheconterminousUnitedStates(exceptwherescenario.otherwisestated)andwithinRPAregions(figure5-1).Thetimeperiodsforsummariesofrecentpasttrendsvaryby❖Extremedroughtsleadtoincreasedwildfiredisturbanceagent,butmostincludedatabeginninginatleastthe1990s,whilefutureprojectionsarefortheperiodactivityinrangelandswhereannualvegetation2020to2070.productionisconsistentlyhigh.WhereaverageproductivityislowbutinterannualvariabilityinFigure5-1.DistributionofforestlandandrangelandinthefourRPAregions.productivityishigh,increasedwildfireactivityoccursfollowingwetperiods.Sources:ThedistributionofforestlandisfromBrooksetal.forestlandusemap(seeLandResourcesChapter);thedistributionofrangelandisfromReevesandMitchell(2011).ForestsFireisadominantdisturbanceagentinmanytypesofforestsintermsofareaaffected,theextentoftreedamageandmortality,andresultingeffectsonforestresourcesandecosystemservices(PausasandKeeley2019,ThomandSeidl2016).Atthesametime,fireisanaturalandintegralfeatureofforestecosystems,manyofwhichareadaptedtoparticularregimesoffirefrequency,intensity,severity,andseasonality(GreenbergandCollins2021).Beginninginthefirsthalfofthe20thcenturyanduntilthe1950s,theaverageannualareaofforestburnedbyallfiresintheUnitedStatesdecreased,althoughyear-to-yearvariabilityinburnedarearemained(Littelletal.2009,Parisienetal.2016,vanWagtendonk2007).Thisdecreaseinaverageburnedareadisruptednaturalfireregimesinmanypartsofthecountry,leadingtoaccumulationofpotentialfirefuelsandleavingsomeforestecosystemsvulnerabletolargerandmoreseverefuturefires(Abatzoglouetal.2017,Calkinetal.2015,Parisienetal.2016).Theexpansioninmanyforestedregionsofthewildland-urbaninterface(WUI),wherehumandevelopmentandnaturallandsmeetorintermix,hasincreasedchancesofhuman-causedfire5-2FutureofAmerica’sForestsandRangelandsignitionsandresultedingreatereconomicimpacts(e.g.,onalllands(notjustforest)intheUnitedStates—thelargestpropertydamageandloss)andlossofhumanlife(Calkinburnedareainasingleyear,andmostofthatareaoccurredinetal.2014,Radeloffetal.2018)(seetheLandResourcestheRockyMountainandPacificCoastRegions(HooverandChapter).AwarmingclimateisexpectedtomagnifyHanson2021).Thelargeburnedareain2020hasbeenlinkedwildfireactivity,includingmoreextremewildfireeventstodryatmosphericconditionsandahighervaporpressureasdroughtsbecomemorelikely(AbatzoglouandWilliamsdeficit,whichledtodrierfuelsthatcouldignitemore2016,Barberoetal.2015,Littelletal.2016).easily;climatechangewasasubstantialcontributortothoseconditions(HigueraandAbatzoglou2020).Trendsintotalforestareaburnedbylargefires(definedasfiresatleast405hainsizeintheWesternUnitedStatesWhilethelargefiressummarizedabovecanincludesomeand202haintheEast)andburnseverityshownotableprescribedfires,manyprescribedfiresaresmallerinextentdifferencesovertimeandbyregion(figure5-2).Acrossthethanthecutoffforlargefires,andarethuslargelyexcludedconterminousUnitedStates,theannualforestareaburnedfromtheanalysisoflargefires(Nowelletal.2018).Inbylargefireshasshownanincreasingtrend.Between1984addition,prescribedfiresconductedbyStateagenciesareand2000,burnedforestareaintheUnitedStatesaveragedexplicitlyexcludedfromthelarge-firedataset(Picotteet334,000haperyear(about0.13percentoftotalforestal.2020).Prescribedfireisthepracticeofusingfireforarea).Since2000,theburnedforestareaaveraged965,000managementpurposes,includingmaintainingorrestoringhaperyear(about0.37percentoftotalforestarea),ecologicalconditions,helpingforestsadapttochangingrepresentinga189-percentincrease,ornearlytriplethebiophysicalandclimaticconditions,andreducingtheriskpre-2000average.Thissametrendisseenattheregionalofwildfiresinfire-proneforests(HunterandRobles2020,scale,exceptfortheRPANorthRegion,butburnedareaKrofchecketal.2018,Ryanetal.2013).Insomeforestalsovarieswidelyforeachregionfromyeartoyear.Overecosystems,itisthereforetheabsenceoffire,ratherthantheentiretimeperiod,thegreatestareaoflargefiresprescribedfire,thatdisruptsanecosystem’sdynamicsandoccurredinthetwowesternRPAregions(PacificCoastcanbeconsidereda“disturbance”totheecosystem(e.g.,andRockyMountain).Since2000,burnedareaaveragedFilletal.2015).Becauseprescribedfiresareimportantto259,000haperyearinthePacificCoastand403,000haperthedynamicsofforestsacrossthecountry,wesummarizeyearintheRockyMountainRegion,representingincreasesprescribedfireusebyregiontocomplementthesummaryof165percentand219percentoverthepre-2000average,oflarge-fireareas.respectively.Thosetworegionsalsohadthegreatestareasofmoderate-andhigh-severityfiresinallyears.TheRPANationallyconsistent,comprehensivedataonthelocationsSouthRegionexperienceda271-percentincrease,toanandseveritiesofprescribedfiresinforestsaredifficultaverageof286,000haperyearburnedsince2000—atoobtain(Nowelletal.2018;butseeHawbakeretal.largerproportionalincreasethanthetwowesternregions—2017,2020).However,resultsfromarecentStatesurveyhowevermoderate-andhigh-severityfireswererare.Inonprescribedburningactivitiesshowthatapproximatelycontrast,therehasbeenrelativelylittlelarge-fireactivity3.68millionhaofprescribedfireswereconductedinonforestlandsintheNorthRegionduringtheperiodof2017forforestryobjectivesnationwide(Melvin2018).record.ManyofthefiresintheNorthRegionarerelativelyThetreatedareaincreasedslightlyfrom3.37millionhasmallprescribedfiresconductedbymanagementagenciesintheoriginal2011surveyconducted,andcontinuedtoandthusnotincludedhere(seethefollowingparagraphs).increasein2018and2019(Melvin2021).Mostofthe2017Onaverage,theareaofhigh-severityfireshasincreasedarea(2.35millionha,64percentofthetotal)occurredinacrosstheUnitedStatessince2000,with141,000haoftheRPASouthRegion(Melvin2018),supportingotherhigh-severityfiresburningannuallysince2000,comparedrecentstudiesthathighlightedthegeneralimportanceandwith48,000haannuallypriorto2000.TheshareofthewidespreadnatureofprescribedburninginforestsinthetotalareaoflargefiresclassifiedashighseverityremainedSoutheasternUnitedStates(Mitchelletal.2014,Nowellapproximatelyunchangedbetweenthetwoperiods,etal.2018).SeethesidebarCOVID-19asaConstraintonaveraging14.4percentpriorto2000and14.6percentsincePrescribedBurningintheSoutheasternUnitedStatesfor2000.Thisincreaseinareabutnotinproportionofthetotaldiscussionofsomerecentchallengesinapplyingprescribedcorroboratesotherassessments(e.g.,Voseetal.2018).fireintheSoutheast.Importantly,theareasreportedlytreatedbyprescribedfireexceedtheareaofforestaffectedSince2017,theUnitedStates,andespeciallytheRockybylargewildfiresinanysingleyearofthewildfiredataMountainandPacificCoastRegions,havesetseveralrecordssummarizedhere,forthecountryasawholeandfortheforareasburned.In2020,morethan4.1millionhaburnedSouthRegion.2020ResourcesPlanningActAssessment5-3Figure5-2.Percentandareaofforestburnedbylargefires(atleast405haintheWesternUnitedStatesand202haintheEasternUnitedStates)overtimebyburnseveritycategory.The“other”categorycombinestheseveritycategoriesofunderburnedtolowseverity,lowseverity,andincreasedpost-firegreenness/vegetationresponse.ha=hectares.Source:MonitoringTrendsinBurnSeverity(MTBS,Eidenshinketal.2007,Picotteetal.2020).5-4FutureofAmerica’sForestsandRangelandsCOVID-19asaConstraintonPrescribedBurningintheSoutheasternUnitedStatesPrescribedfireisanessentialmanagementtoolformanydeclineinactivefireswasimmediatelyobservedaslandmanagementobjectivesandacrossawidediversityofFederalandStateagenciesandprivatelandownersadaptedSoutheasternecosystems.Therearediverseimpedimentstotowork-from-homeorders(Figure5-3,Poulteretal.applyingfireintheSoutheast,includingsmokemanagement,2021).FollowinganexceptionallywetFebruary,activelimitedresources,andpublicapproval(Kobziaretal.2015).firesincreasedforthefirsthalfofMarch,butthendeclinedBeginninginMarch2020,theCOVID-19pandemicledtoabruptlyinmid-Marchandfortheremainderof2020.Instay-at-homeandshutdownordersacrosstheworld.Almostsomecases,landmanagershaltedprescribedfireprogramsimmediately,hypothesesemergedonhowCOVID-19wouldtoavoidcreatingsmokeconditionsthatmightexacerbateaffectallcomponentsoftheEarthsystem(Diffenbaughethealthproblems.Inothercases,firecrewswereunabletoal.2020).TobegintodeterminetheeffectsofCOVID-19workbecauseofCOVID-19safetyregulations,orbecauseonmanagedfireintheSoutheast,weexaminedtherecordofstaffshortagesascrewmemberswereinfected(Cahanofactivefires—thatis,firesthatweredetectedwhenNASA2020).Insummerandfall2020,anotableshiftinthesatellitespassedoverhead.seasonaltimingofprescribedfireapplicationonalllandsAFigure5-3.ActivefiresdetectedbysatellitesintheSoutheasternUnitedStates.Thetoptwopanelsshowcumulativeweeklyactivefirecountsbyyear(2003to2020)foralllands(left)andFederallandsonly(right).ThebottomtwopanelsshowthechangeinthenumberofactivefiresinApril2020comparedwiththe18-yearaverageforalllands(left)andFederallandsonly(right),withfewerfiresthanaverageinblueandmorefiresthanaverageinred.Inthetoppanels,theverticalblacklineindicatesMarch15,theapproximatedateofCOVID-19stay-at-homeordersin2020.Inthebottompanels,blackoutlinesindicateFederallands,whicharethoseownedbytheU.S.DepartmentsofInterior,Defense,orAgriculture.Activefiresaredefinedasplaceswhereafirewasburningwhenasatellitepassedoverhead.CumulativeMODISactivefirecounts(#)Changeinactivefires(#/month)Source:MODISinstrumentontheNASAAQUAandTERRAsatellites.2020ResourcesPlanningActAssessment5-5occurredinresponsetoCOVID-19,withincreasesinlate-Thus,thechallengesinconductingburningduetoCOVID-19yearburningtocompensateforlostburned-acreageduringtheaddedtoanalreadyexpandingbacklogofprescribedfirespring.Bytheendof2020,thenumberofactivefireswas21acreageintheSoutheastasCOVID-19continuedinto2021.percentbelowthe20-yearaverageforallprivateandpublicInthenearterm,ecosystemsandplantandanimalspeciesthatlands,and41percentbelowthe20-yearaverageforfederallyarelinkedtofrequentfire(includingfederallylistedspecies)ownedlands.Thislargereductionandseasonalshiftinactivemaysufferfromthereducedhabitatqualitycausedbyreducedfiredetectedinthesatelliterecordwasconfirmedtocomefireextent.WildfirehazardreductioneffortsontheselandsfromareductioninmanagedfiresbasedontheIntegratedhavealsobeenstalled,potentiallyexacerbatingfuturewildfireInteragencyFuelsTreatmentDatabase(IIFT,https://iftdss.threats.Movingforward,managersfacethechallengeoffirenet.gov/).“catchingup”onthebacklogwhileconfrontingtheneedtomaintainspecies,broaderecosystemprocesses,andfirehazardThereductioninmanagedfiresin2020followsadeclineinreductiontargetsacrosstheregion.early2019whentheFederalgovernmentwasshutdown.Futuretrendsinvolumesoftreemortalityfromwildfireswereovertime,includingbasalarea,downwoodymaterialthatsummarizedfromRPAForestDynamicsModelresults(seecanactasfuels,standage,speciescomposition,andharvesttheForestResourcesChapter)fortheRPAscenarios(seeprobability.BecauseofthelimitedabilityofFIAfieldcrewsthesidebarRPAScenarios).TheForestDynamicsModeltodetectlow-severityfires,firesthatdonotleadtotreeprojectsthefutureforestinventory,includingvolumesandmortalityareomittedfromtheForestDynamicsModel.Thus,areasofforestbyRPAregionandforesttypegroup,forwardtheprojectionscanbeusedtoexaminechangesinannualintimeforthe20RPAscenario-climatefutures(fourRPAmortalityvolumefromfireandchangesinareasburnedbyscenarios,fiveclimateprojections).Asubmodelprojectsmoderate-andhigh-severityfires,buttheydonotprovidethefuturefireoccurrenceandtreemortalityresultingfromestimatesoftotalburnedareas.MoreinformationaboutthefirebasedonForestInventoryandAnalysis(FIA)dataandForestDynamicsModelcanbefoundintheForestResourceslinkstoothersubmodelsthatmodifyforestcharacteristicsChapterandinCoulstonetal.(inpreparation).RPAScenariosTheRPAAssessmentusesasetofscenariosofcoordinatedinfourdistinctfuturesthatvaryacrossamultitudeoffutureclimate,population,andsocioeconomicchangetocharacteristics(figure5-5),andprovidingaunifyingprojectresourceavailabilityandconditionoverthenext50frameworkthatorganizestheRPAAssessmentnaturalyears.Thesescenariosprovideaframeworkforobjectivelyevaluatingaplausiblerangeoffutureresourceoutcomes.Figure5-4.Characterizationofthe2020RPAAssessmentscenariosintermsoffuturechangesinatmosphericwarmingandU.S.The2020RPAAssessmentdrawsfromtheglobalsocioeconomicgrowth.ThesecharacteristicsareassociatedwithscenariosdevelopedbytheIntergovernmentalPanelthefourunderlyingRepresentativeConcentrationPathway(RCP)–onClimateChangetoexaminethe2020to2070timeSharedSocioeconomicPathway(SSP)combinations.period(IPCC2014).TheRPAscenariospairtwoalternativeclimatefutures(RepresentativeConcentrationSource:Langneretal.2020.PathwaysorRCPs)withfouralternativesocioeconomicfutures(SharedSocioeconomicPathwaysorSSPs)inthefollowingcombinations:RCP4.5andSSP1(lowerwarming-moderateU.S.growth,LM),RCP8.5andSSP3(highwarming-lowU.S.growth,HL),RCP8.5andSSP2(highwarming-moderateU.S.growth,HM),andRCP8.5andSSP5(highwarming-highU.S.growth,HH)(figure5-4).Thefour2020RPAAssessmentscenariosencompasstheprojectedrangeofclimatechangefromtheRCPsandprojectedquantitativeandqualitativerangeofsocioeconomicchangefromtheSSPs,resulting5-6FutureofAmerica’sForestsandRangelandsFigure5-5.Characteristicsdifferentiatingthe2020RPAAssessmentscenarios.ThesecharacteristicsareassociatedwiththefourunderlyingRepresentativeConcentrationPathway(RCP)–SharedSocioeconomicPathway(SSP)combinations.resourcesectoranalysesaroundaconsistentsetofpossibleUnitedStates(table5-1);however,characteristicscanworldviews.TheScenariosChapterdescribeshowthesevaryatfinerspatialscales.Althoughthesamemodelsscenarioswereselectedandpaired;moredetailsarewereselectedtodevelopclimateprojectionsforbothprovidedinLangneretal.(2020).lowerandhigh-warmingfutures,therearedistinctclimateprojectionsforeachmodelassociatedwithRCPThe2020RPAAssessmentpairsthesefourRPA4.5andRCP8.5.TheScenariosChapterdescribeshowscenarioswithfivedifferentclimatemodelsthatcapturetheseclimatemodelswereselected.JoyceandCoulsonthewiderangeofprojectedfuturetemperatureand(2020)giveamoreextensiveexplanation.precipitationacrosstheconterminousUnitedStates.AnensembleclimateprojectionthataveragesacrosstheThroughouttheRPAAssessment,individualscenario-multiplemodelprojectionsisnotusedbecauseoftheclimatefuturesarereferredtobypairingRPAscenariosimportanceofpreservingindividualmodelvariabilitywithselectedclimateprojections.Forexample,ananalysisforresourcemodelingefforts.Thefiveclimatemodelsrununder“HL-wet”assumesafuturewithhighatmosphericselectedbyRPArepresentleastwarm,hot,dry,wet,andwarmingandlowU.S.populationandeconomicgrowthmiddle-of-the-roadclimatefuturesfortheconterminous(HLRPAscenario),aswellasawetterclimatefortheconterminousUnitedStates(wetclimateprojection).Table5-1.Fiveclimatemodelsselectedtoreflecttherangeofthefullsetof20climatemodelsintheyear2070.EachmodelwasrununderRCP4.5andRCP8.5,providingarangeofdifferentU.S.climateprojections.ClimatemodelLeastwarmHotDryWetMiddleInstitutionIPSL-CM5A-MRNorESM1-MMRI-CGCM3HadGEM2-ESCNRM-CM5InstitutPierreSimonNorwegianClimateMeteorologicalMetOfficeHadleyLaplace,FranceNationalCentreCenter,NorwayResearchInstitute,Centre,UnitedofMeteorologicalKingdomResearch,FranceJapanRCP=RepresentativeConcentrationPathway.Source:JoyceandCoulson2020.2020ResourcesPlanningActAssessment5-7Annualfiremortalityvolumeisprojectedtoincreaseovertimethreehigh-warmingRPAscenarios(HL,HM,andHH).TheacrosstheUnitedStatesandineachRPAregionunderall20smallestincreaseswereprojectedfortheleastwarmclimatescenario-climatefutures(figure5-6)—from40millioncubicprojectionregardlessoftheRPAscenario.Theseprojectionsmetersin2020(0.10percentoftotallivevolumeinallforests)generallyagreewithstudiesthatpointtoexpectedincreasesintobetween62millioncubicmetersunderLM-leastwarm(thefireoccurrenceovermuchofthecountry,especiallyasclimateLMscenarioandleastwarmclimatemodel)and84millionbecomeswarmeranddrier(Gaoetal.2021,Littelletal.2016).cubicmetersunderHM-dry(theHMscenarioanddryclimateWhileasubstantialincreaseinfiremortalityvolumewasmodel)in2070,representinganincreaseofbetween55and108projected,thecombinedaverageannualvolumeofremovalspercentrelativeto2020values.TheresultthatallfuturesprojectfortimberharvestinFlorida,Georgia,NorthCarolina,andthesamedirectionalchangeindicatesrelativelylowuncertaintySouthCarolinatotaledjustover86millioncubicmetersin2016intheimpactoffutureclimateandsocioeconomicchangeon(Oswaltetal.2019),slightlyexceedingthemostextremefirefiremortalityvolume.Generally,thegreatestincreasesinfiremortalityvolumeprojectionfortheconterminousUnitedStatesmortalityvolumeby2070wereprojectedforplausiblefuturesin2070(84millioncubicmeters).thatincludedthedryorhotclimateprojectionsundertheFigure5-6.ProjectedannualfiremortalityvolumeovertimeforallRPAscenarios.ResultssummarizeoutputfromForestDynamicsModelsimulations(seetheForestResourcesChapterformoredetailsonthemodel).Ineachpanel,thedarklinesrepresentthemedianoutcomeof100simulations,andtheshadedarearepresentstheinter-quartilerangeofthosesimulations.Theright-handverticalaxisshowsthevaluesintermsofpercentoftotallivevolumein2020.Bothverticalaxesapplytoallfourpanels.Becausethetotallivevolumeofforestsisexpectedtoincreaseovertime(seetheForestResourcesChapter),thevolumekilledbyfirerepresentsalowerproportionofthetotalvolumein2070thanisdisplayed.LeastWarmHotDryWetMiddleLM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.5-8FutureofAmerica’sForestsandRangelandsTheexpectedtrendsinannualfiremortalityvolumewithinthetwowesternregionscurrentlyandthroughoutthefutureRPAregionsmirrorthenationwidetrend,withincreasesperiod,anincreaseof184to505percent,tobetween10projectedinallregions.Therelativemagnitudesofincreaseand22millioncubicm,isprojectedby2070.IntheNorthdifferbyregion,andtheprojectedchangesinforestandfireRegion,wherethereisverylittlefireactivity,annualfiredynamicsthatresultinincreasedvolumedifferslightlybymortalityvolumeisexpectedtoincreaseaswell,butremainregion.IntheRockyMountainRegion,firemortalityvolumelowerthanallthreeotherregions.Increasestobetween1.2isexpectedtoincreasebetween20and55percent,fromand2.0millioncubicmareprojectedby2070.22millioncubicmin2020tobetween26and34millioncubicmby2070(table5-2,figure5-7).InthePacificCoastAprojectedincreaseinannualtreevolumekilledbyfireinRegion,annualfiremortalityvolumein2020waslowerthanaregioncanbeduetoanincreaseintheareaburnedbyfire,intheRockyMountainRegion,butisexpectedtoincreaseanincreaseintheproportionoflivevolumeinburnedforesttoaleveleitherslightlybeloworcomparabletotheRockystandsthatiskilledbyfire,oracombinationofbothfactors.MountainRegionby2070—fromapproximately14millionIntheRockyMountainRegion,theannualareaofmoderate-cubicmin2020tobetween24and29millioncubicminseverityfires(between30-and70-percentmortalityby2070,representinga63-to100-percentincrease.Inthevolume)isexpectedtomorethandoublefrom2020to2070South,whilefiremortalityvolumeisloweroverallthanin(108-to179-percentincrease)(table5-2),whileprojectionsFigure5-7.AnnualfiremortalityvolumeforRPAregionsin2020andprojectedin2070forallRPAscenarios.ResultssummarizeoutputfromForestDynamicsModelsimulations(seetheForestResourcesChapterformoredetailsonthemodel).Forthevaluesin2070,dotsrepresentthemeanofthefiveRPAclimateprojectionsundereachRPAscenario,whileverticalbarsindicatetherangeofvaluesacrossthoseclimateprojections.LM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.2020ResourcesPlanningActAssessment5-9Table5-2.Projectedchangesfrom2020to2070(valueandpercentchange)inoverallannualfiremortalityvolume,firemortalityvolumeasapercentoftotalvolumeinburnedlocations,andannualareasofmoderate-andhigh-severityfiresforeachRPAregion.Moderate-severityfiresaredefinedasthosethatkill30to70percentofvolume,whilehigh-severityfireskilledatleast70percentofvolume.Thefirstcolumnundereachvariableindicatestheabsolutechange,andthesecondcolumnindicatesthepercentchangeby2070over2020values.ChangeinfiremortalityChangeinareaofmoderate-Changeinareaofhigh-Aspercentofvolumeinvolumeseverityfiresseverityfiresburnedlocationsmillionm3percenthapercenthapercentpercentagepercentpointsNorth0.83-1.6196-3856,000-11,000483-884-1,300-4,800-16-62-3.4--2.5-19--14South6.6-18.2184-50512,000-54,00072-33019,000-70,00070-256RockyMountain4.4-12.020-5546,000-76,000108-179-3,300-34,000-2-240.4-3.52-17PacificCoast9.1-14.463-10040,000-53,000141-18536,000-49,00069-95-10.0--7.1-16--122.9-3.96-8ha=hectares;m3=cubicmeters.ofhigh-severityfires(atleast70percentmortalitybytypegroup(figures5-9,5-10).Severalofthewesterntypevolume)showeitherdecreasesorsmallincreasesinannualgroupsthathavehighormoderateannualfiremortalityareas.Inotherwords,underallscenarios,theannualareavolumesin2020areexpectedtoexperiencelargeincreasesofmoderate-severityfiresintheRockyMountainRegionunderallRPAscenarios,includingDouglas-fir,ponderosaisprojectedtoincreasemorethantheareaofhigh-severitypine,woodlandhardwoods,andpinyon/juniper,andfiresbetween2020and2070.Theoverallaverageannualtheannualareaofhigh-severityfiresisalsoexpectedtoproportionoflivevolumekilledbyfireinlocationsthatincreaseinthosegroups(figure5-9).Thelatterthreeofburnedisexpectedtodecrease12to16percentoverthatthosegroupseachoccur,atleastinpart,inrelativelydrytimeintheregion(table5-2).InthePacificCoastandSouthportionsoftheSouthCentralandSouthwesternUnitedRegions,theprojectedannualareasofbothmoderate-andStates,wheredryconditionsareexpectedtobecomemorehigh-severityfiresincreaseby2070,alongwiththeaveragecommoninthefuture(seethesectionDroughtinForestsproportionofvolumekilled(table5-2).Whilefewstudieshaveexaminedprojectedtrendsinfireseverity,mostFigure5-8.AreaofforestforeachforesttypegroupintheFIAdatabase,researchhassuggestedthepotentialforhigherfireseveritycirca2013.AllanalysisinthischapterthatwasbasedonFIAdataexcludedasclimatechanges,includingportionsoftheWesternUnitednonstocked,exotic,andtropicalgroups,andtwoothersthatwerelimitedinStates(Halofskyetal.2020,VanMantgemetal.2016),andextent:thewesternwhitepineandredwoodtypegroups.increasesinthenumberofextremefireeventsinportionsoftheSouth(Terandoetal.2017).ThatalignswithourresultsFIA=ForestInventoryandAnalysis;ha=hectares.ha(millions)forthePacificCoastandSouth,butour2070projectionofeitheranincreaseoradecreaseinareaofhigh-severityfiresfortheRockyMountainRegionhighlightstheuncertaintyassociatedwithprojectingfireseverity.Parksetal.(2016)modeledfuturefireseverityfortheWesternStatesandprojectedthepotentialforlowerfireseverityformostoftheWest,includingtheRockyMountains,ifvegetationchangesoccurthatresultinreducedfuels.However,futurechangestofuellevelsarehighlyuncertainanddependonmanyfactors,includingclimate,forestproductivity,management,andfirehistory.EachRPAregionisheterogeneousandcontainsforestscharacterizedbymorefrequent,low-severityfires,aswellasthosecharacterizedbylessfrequent,moderate-orhigh-severityfires(GreenbergandCollins2021,Schoennageletal.2004).Understandingtheprojecteddynamicsoffirewithineachtypeofforest(figure5-8)canprovideinsightsintothepotentialeffectsoffuturefireonthoseforests.Mostforesttypegroupsareexpectedtohavegreaterfiremortalityvolumesby2070comparedwith2020,althoughthemagnitudeofincreaseisexpectedtovarybyforest5-10FutureofAmerica’sForestsandRangelandsandRangelands).Muchoralloftheextentsofthosetypeisonenotableforesttypegroupwithlowerprojectedfiregroupsarecharacterizedbyrelativelylowlivevolumesandmortalityvolumein2070thanin2020.Theaverageannualfrequent,low-severityfireregimesthatkillfewtrees,butinareaofhigh-severityfiresinthelodgepolepinetypegroupismanyplacesthosefireregimeshaveshiftedtowardhigher-alsoprojectedtodecrease(figure5-9),accountingformuchseverityfires(GreenbergandCollins2021).Anincreaseinofthedeclineinfiremortalityvolume.theareaofhigh-severityfirescouldthereforefurtherthreatenthoseforestecosystems.Douglas-firforestsarehistoricallyForesttypegroupsfoundpredominantlyintheEastarecharacterizedbylessfrequent,higherseverityfires,andexpectedtoseerelativelymodestchangesinfiretreetheexpectedincreaseinfiremortalityvolume,alongwithmortalityvolume(figure5-10).Oneexceptionistheoak/increasingareaofhigh-severityfires,couldimplymorehickoryforesttypegroup,whosefiremortalityvolumefrequentseverefiresinthatforesttype.Lodgepolepineisprojectedtoatleastdoubleby2070andwhoseannualFigure5-9.Annualfiremortalityvolumeforwesternforesttypegroupsin2020andprojectedin2070forallRPAscenarios.ResultssummarizeoutputfromRPAForestDynamicsModelsimulations(seetheForestResourcesChapterformoredetailsonthemodel).Forthevaluesin2070,dotsrepresentthemeanofthefiveRPAclimateprojectionsundereachRPAscenario,whileverticalbarsindicatetherangeofvaluesacrossthoseclimateprojections.Foresttypegroupsarearrangedaccordingtotheir2020observedannualfiremortalityvolume(highestatthetoplefttolowestatthebottomright).Plusesandminusesinparenthesesaftereachforesttypegroupnameindicateanincrease(+)ordecrease(-)inannualareaofhigh-severityfireprojectedby2070,definedasfiresthatresultinatleast70percentoflivevolumekilled,orwhetheranincreasewasprojectedforsomefuturesandadecreasewasprojectedforothers(-/+).LM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.2020ResourcesPlanningActAssessment5-11areaofhigh-severityfiresisprojectedtoincreaseinallthatforesttype.However,anincreaseintheareaofhigh-futures.Oak/hickoryforests,likemanyforesttypesintheseverityfirescouldfurtheraltertheoak/hickoryforestEasternUnitedStates,havebeenexperiencingreducedecosystems.frequencyandincreasedseverityoffirerelativetohistoricalconditions,whenfiresburnedfrequentlyandresultedinlowTheprojectedchangesinfiremortalityvolumesoftreestreemortality(NowackiandAbrams2008).Asaresult,oak/providesomeinsightsintothechangingdynamicsoffirehickoryforestshaverecentlydeclined.WhilethespecificinU.S.forests.Inadditiontodirecteffectsonforestslocalecologicaleffectsoffiredependonmanyfactors,anthemselves,increasesinfiremortalityvolumeandhigh-increaseinfiremortalityvolumecouldbebeneficialtooak/severityfiresalsohaveimplicationsforhumanhealthhickoryforestsintheEastifitsignalsmorefireoverallinandpropertyinthewildland-urbaninterface(WUI)andFigure5-10.Annualfiremortalityvolumeforeasternforesttypegroupsin2020,andprojectedin2070forallRPAscenarios.ResultssummarizeoutputfromRPAForestDynamicsModelsimulations(seetheForestResourcesChapterformoredetailsonthemodel).Forthevaluesin2070,dotsrepresentthemeanofthefiveRPAclimateprojectionsundereachRPAscenario,whileverticalbarsindicatetherangeofvaluesacrossthoseclimateprojections.Foresttypegroupsarearrangedaccordingtotheir2020observedannualfiremortalityvolume(highestatthetoplefttolowestatthebottomright).Plusesandminusesinparenthesesaftereachforesttypegroupnameindicateanincrease(+)ordecrease(-)inannualareaofhigh-severityfireprojectedby2070,definedasfiresthatresultinatleast70percentoflivevolumekilled,orwhetheranincreasewasprojectedforsomefuturesandadecreasewasprojectedforothers(-/+).Thespruce/firandlongleaf/slashpineforesttypegroupshadnohigh-severityfireprojectedin2020or2070.LM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.5-12FutureofAmerica’sForestsandRangelandsbeyond.ExpansionoftheWUIandincreasingfireactivityincreasedover300percentfromthepre-2000amountstoarealreadycontributingtolossofhumanlifeandproperty168,000haperyear,andthe2011fireseasonproducedfromfire,presentingchallengesforfiresuppressionandthelargestburnedareaintherecordfortheregion,withincreasingcostsassociatedwithsuppression(Abtetal.over800,000haburnedthatyear(over2.0percentofthe2009,Radeloffetal.2018).Theincreasesinhigh-severitySouth’srangelandarea).OnlytheNorthRegion,whichhasfiresprojectedinmostregionsandforesttypescouldaddarelativelysmallamountofrangelandarea(approximatelytothosealready-substantialchallengesandcostsoffire6.1millionha),exhibitedadecreasingtrendintheareamanagement.Anysubstantialincreaseinfueltreatments,burnedperyear.suchasthinningorprescribedburning,acrosslargelandscapesorregionscouldresultinreducedfireseverityThenationalandregionalnatureofthisanalysisobscuresandreducedriskoflarge,difficult-to-managefiresinthefine-scalepatternsofwildfiresoccurringinrangelands.someforests.Foresttypessuchasponderosapineforests,Therelationshipsbetweenclimate,fuels,andfireinwhichareadaptedtofrequent,low-severityfiresandrangelandecosystemsarecomplex.Theannualareaburnedhaveexperiencedabuild-upoffuelsresultingfromfireislinkedwithdroughtpatterns,buttherelationshipisnotsuppression,couldespeciallybenefitfromsuchtreatmentslinear,issometimescounterintuitive,variesbyecosystem,(Halofskyetal.2020,Moritzetal.2014,Schoennageletandfirescanoccurmonthsafterdroughthasoccurredal.2004).Furthermore,theseprojectionsdonotinclude(KrawchukandMoritz2011).Droughtscanleadtolargeranychangestofireignitions,suchasincreasednumbersoffiresandagreaternumberoffires,butonlyifsufficienthuman-causedignitionsduringperiodswithhighfirehazardfuelsarepresent(AbatzoglouandKolden2013,Littellet(Balchetal.2017,Fuscoetal.2016)thatcouldoccurintheal.2018).Somerangelandareasconsistentlyhavehighfuture.Additionalignitionscouldincreasefireoccurrencelevelsofvegetationproductivity(figure5-12)andthusfuelsandseverityinsomeforestecosystems(PausasandKeeleyareconsistentlyavailable.Inthoseareasduringdrought2021).Furtherworkcouldincorporateincreasedtreatmentyears,relativelycontinuousfuelscombinedwithlowfuellevelsorchangesinignitionsandfuelavailabilityintothemoistureleadtoextremefirebehaviorandlargeareasRPAForestDynamicsModelandexaminetheeffectsofburned.Forexample,inTexasandOklahomawhereannualthoseonprojectedfiremortalityvolumeandfireseverity.vegetationproductionisconsistentlyhigh,widespreadextremedroughtsoccurredin2011,contributingtothelargeRangelandsrangelandareaburnedintheRPASouthRegionthatyear(figure5-11;alsoseethesectionDroughtinForestsFireplaysanimportantroleinmaintainingvegetationandandRangelands).ensuringforageforlivestockinrangelands(Fuhlendorfetal.2012,Limbetal.2016).WhilefiresarepartoftheInthenorthernGreatPlainsin2011,fireactivitywasnaturaldynamicsofrangelands,invasivegrassesandrelativelylowbecauseofcomparativelycoolandmesicdroughthaveledtomorefrequentandlargerfiresinsomeconditions.Thislowfireactivitycontributedtoamoderaterangelandsystems(AbatzoglouandKolden2011,CoatesareaburnedintheRockyMountainRegionin2011etal.2016).Ananalysisoftherangelandareasburnedby(figure5-11).Thehighprecipitationandhighresultantlargewildfires(againdefinedasfiresatleast405hainannualproductionof2011,however,ledtolargeamountssizeintheWesternUnitedStatesand202haintheEasternofstandingdeadmaterialbytheendoftheyear.WhenUnitedStates)indicatesanincreaseinburnedrangelanddroughtoccurredintheregionthenextyear(2012),thisareafrom1984to2017,distributedasymmetricallyacrosshighamountofstandingdeadmaterialincreasedignitiontheRPAregions.Before2000,burnedareaaveragedaboutpotentialandfirebehavior(Reevesetal.2020).Whilethe470,000haperyear(figure5-11;about0.19percentoftotalareaburnedintheRockyMountainRegionduringrangelandarea).Since2000,thetotalrangelandareaburned2012inouranalysisislowerthanforotheryears(figureperyearincreasedsubstantiallytoanaverageofabout15-11),someofthelargestindividualwildfiresonrecordmillionhaperyear(about0.45percentofrangelandarea),occurredin2012duringrecord-settingheatanddroughtanincreaseof119percentoverthepre-2000average.The(e.g.,theAshCreekComplexinMontana)(Karletal.2012,2006fireseasonproducedthehighestannualareaburnedReevesetal.2020).at2.3millionha(about0.9percentoftherangelandarea).TheRPARockyMountainRegionhadthehighestaverageIncontrasttotheGreatPlains,muchoftherangelandareaannualrangelandareaburnedsince2000(approximatelyoftheWesternUnitedStatestypicallyhasrelativelylow638,000haperyear),followedbythePacificCoastproduction,whichleadstosmallamountsoffuelavailableRegion(218,000haburnedperyear).Inbothregionstheinanaverageyear.However,someareaswithrelativelylowaverageareasburnedincreased100percentoverthepre-productiononaveragetendtoexhibitthegreatestinterannual2000averages.IntheSouthRegion,averageareaburnedvariabilityinproduction,andthushighvariabilityinfuels,especiallyfinefuelslessthan6.35mmindiameter(e.g.,2020ResourcesPlanningActAssessment5-13Figure5-11.Percentandareaofrangelandsburnedbylargefires(atleast405haintheWesternUnitedStatesand202haintheEasternUnitedStates)overtimebyburnseveritycategory.The“other”categorycombinestheseveritycategoriesofunderburnedtolowseverity,lowseverity,andincreasedpost-firegreenness/vegetationresponse.ha=hectares.Source:MonitoringTrendsinBurnSeverity(MTBS,Eidenshinketal.2007,Picotteetal.2020).5-14FutureofAmerica’sForestsandRangelandsFigure5-12.Averageannualproduction(top)andaverageinterannualDroughtinForestsandvariability(bottom)inU.S.rangelandsfrom1984to2020.Rangelands15–476❖ForestsintheRPAPacificCoastRegionhavehad477–647648–1,108higherexposuretodroughtthanotherregions1,109–2,347since2005.2,348–5,681❖RangelandsintheRPAPacificCoastRegionSource:Reevesetal.(2021).1–2526–32havesimilarlyexperiencedhighdroughtexposure33–56since2005,andrangelandexposurewasalso57–137highintheSouthandRockyMountainRegions138–408from2011to2012.grassesandforbs).Theseareasaresubjecttoheatand❖Forestandrangelandexposuretodroughtisdrynessinmostyears.Theecosystemsthatmeetthesecriteria,includingtheSonoranandMojaveDeserts(figureexpectedtointensifyoverthiscentury,particularly5-12),canexperiencesubstantialareasburnedinsomeyearsiftheclimatetendstowardthehot,dry,ormiddlewhenannualproductionexceedsnormal.climatefutures.Thecomplexrelationshipsbetweenclimate,fuels,andfire❖Forestandrangelandvegetationtypesintheinrangelandecosystemsensureacomplexfutureoffireinthosesystems.WhilewedonotincludefireprojectionsSouthwestareprojectedtohavethegreatestforrangelandshere,existingliteratureandknowledgeofdroughtexposureinthefuture,specificallythetheserelationshipsallowsomegeneralstatementsaboutpinyon/juniperwoodlandsforesttypegroup,andpossiblefuturefiretrends.Areastowardtheeasternedgethegrasslandandcreosotebushdesertscruboftherangelanddomainthatproducefuelscontinuouslyrangelandvegetationtypes.buttypicallyhavesurplusmoisturemayhavelargerannualburnedareas,asdryconditionsbecomemorecommonForests(Littelletal.2018).Ontheotherhand,areasthatarefuel-limitedandrequirewetyearstoproducefire,aremorelikelyDrought,animportantstressoraffectingforests,istohavevariationinfireactivityfromyeartoyearbecausecommonlydefinedasaperiodofmoisturedeficitresultinginterannualvariabilityofherbaceousvegetationproductionfrombelow-averageprecipitation,hightemperatures,orisexpectedtoincreaseinthefuture(Klemmetal.2020,both(Clarketal.2016).AloneorincombinationwithReevesetal.2017).otherdisturbances,droughtcanreduceforestproductivity,causeshiftsinforesttypes,affecttheabilityofforeststoregenerate,anddiminishthecapacityofforeststoprovideecosystemservices(Andereggetal.2013,Desprez-Loustauetal.2006,Jacteletal.2012,Petersetal.2015,Trouetetal.2010,Voseetal.2016).Asclimatewarmsandmanypartsoftheworldbecomedrier,droughtsareexpectedtobecomemorewidespread,frequent,andsevere(Ahmadalipouretal.2017,Cooketal.2015,Dai2011,2013,Prudhommeetal.2014,SwainandHayhoe2015).Whiletheeffectsofdroughtontreesandindividualforeststandshavebeendemonstratedforlocalareas,itisdifficulttobothmeasuremoistureconditionsinsituanddeterminethedirecteffectsofdroughtonforestsacrossbroadgeographicregions(Bennettetal.2015,Clarketal.2016,Gazoletal.2018).Manyscientiststhereforeusemeteorologicaldroughtindices,whichtrackrelativedeparturefromnormalclimateconditionsandcanbecorrelatedwithresultingeffectsonforests(Druckenbrodetal.2019).Meteorologicaldroughtindicesaredistinctfromothermeasuresofdrought,includinghydrologicdrought,whichtracksreductionsinwatersupplytoriversandlakes.Informationonwhereandwhenforestshavebeenexposedtometeorologicaldroughtinthepastorarelikelytobeexposedinthefuturecanbeusedtoinformwheremanagementactionorfurtherresearchiswarranted.2020ResourcesPlanningActAssessment5-15WeusetheStandardizedPrecipitationEvapotranspirationshownhere,PETwascalculatedusingthestandardmethodIndex(SPEI)tosummarizerecentandfuturetrendsinrecommendedbyworldorganizations(Abatzoglou2013,droughtexposureforforestlandintheconterminousUnitedAllenetal.1998).However,forsummariesofobservedStates(Costanzaetal.2022a,2022b;fordetailsonSPEI,SPEI(figure5-13),calculationofPETviathepreferredseeBegueríaetal.2014,Vicente-Serranoetal.2010).Themethodwasnotpossiblebecauseofdatalimitations,andweSPEIallowsforcomparisonsamonglocationsforhistoricalusedanalternativemethodthathasbeenrecommendedinaswellasfutureconditions,andcanbecomputedoversuchcircumstancesbutmayoverestimatedryconditionsinmultipletimescales,makingitusefulformonitoringdroughtplaceswithseasonallyhumidclimate(Begueríaetal.2014,indifferentecologicalcontexts(Ault2020,Sletteetal.Hargreaves1994).2019,Vicente-Serranoetal.2010).Weusedthe36-monthSPEI,whichassignsvaluesforagivenmonthbycomparingThemajortrendsinobservedSPEIvalues(figure5-13)thecumulativeclimaticwaterbalance(precipitationminuscorroborateknownincidenceofpastdrought,includingpotentialevapotranspiration,orPET)fortheprevious36droughtperiodsinthe1950sacrossmuchoftheRPASouthmonthstothesamecumulative36-monthwaterbalanceforandRockyMountainRegions(Andreadisetal.2005,Heimallmonthsinareferenceperiod(definedhereas1950to2017)andinthe1960sacrossmuchoftheNorthRegion2005).Prolongeddroughtsthatpersistformultipleyearsare(Barlowetal.2001,Namias1966).Since2005,theNation’smorelikelytocauselastingimpactstoforeststhanshorter-forestshaveexperiencedrelativelyevenproportionsofdrytermdroughtsofequalmagnitude(BerdanierandClarkandwetconditions,althoughregionallytherehasbeenmore2016,Bigleretal.2006,GuarínandTaylor2005,Jenkinsvariationfromyeartoyear.Forexample,thePacificCoastandPallardy1995,Millaretal.2007).FormostoftheresultsRegionwasexceptionallydryonforestlandsduringthemid-2010s,aperiodthathasbeenshowntobedrierthananyFigure5-13.Proportionofforestlandareaincategoriesofobserved36-monthSPEIovertime,basedonPRISMclimatedata,1953to2018,fortheUnitedStatesandRPAregions.TheperiodtotheleftofthedashedlineineachgraphindicatesthereferenceperiodthatwasusedtocalibrateSPEIvalues.SPEI>2,Extremelywet0.5<SPEI<1,Slightlywet-1.5<SPEI<-1,Moderatedrought1.5<SPEI<2,Severelywet-0.5<SPEI<0.5,Nearnormal-2<SPEI<-1.5,Severedrought1<SPEI<1.5,Moderatelywet-1<SPEI<-0.5,SlightlydrySPEI<-2,ExtremedroughtSPEI=StandardizedPrecipitationEvapotranspirationIndex.Source:Costanzaetal.2022b.5-16FutureofAmerica’sForestsandRangelandshistoricalprecedentinCalifornia(Robeson2015),andwhichatmorethan75percent,usingatleastoneclimateprojectioncorrespondedwithhighwildfireactivityandinsectoutbreaksunderRCP8.5.Severalofthetypegroupshavingthehighestintheregion(Fettigetal.2019,Halofskyetal.2020,Marlierprojectedfutureexposures,includingpinyon/juniperandetal.2017,Pileetal.2019).Incontrast,theNorthRegionwasponderosapine,occurinthealready-aridSouthwesternUnitedrelativelywetnearlyeverymonthsince2005(figure5-13).States;ourresultsagreewithotherassessmentsshowingtheObscuredintheseregionaltrendsarelocalizeddroughteventspotentialforunprecedenteddroughtandresultingecologicalthatweresmalleringeographicextentbuthadsubstantialimpactstoforestsintheSouthwesttowardthelatterhalfofforestimpacts,includinghighratesoftreemortalityandthiscentury(Cayanetal.2010,Cooketal.2015,Jiangetal.growthdeclines(seethesidebarVulnerabilitytoDroughtfor2013,Seageretal.2007,Thorneetal.2018,Williamsetal.anexample).2013,2020).Bymid-century,theprojectedrangeofdroughtexposureforeachforesttypegroupreflectsnotonlythewideForestSPEIprojectionsprovideanoutlookonforestdroughtselectionofRPAclimateprojections—leastwarm,hot,dry,exposureunder10differentplausibleclimatefuturesacrosswet,middle—butalsothegeographicrangeoftheforesttypetheUnitedStates.TheintegratedRPAscenarioswerenotgroup.Planningforadryorahotfutureatthelocalscalemayusedfortheseprojectionsduetoaninabilitytoapplythebeimportanttoaddressthepotentialrisktotheresourcesinsocioeconomicfactors,butwedidapplytheclimatefuturestheseforesttypes.However,itisimportanttonotethattheandclimateprojectionsselectedbyRPA(twoRCPs,fiveSPEIindexofexposuredoesnotcapturetheactualwaterclimateprojections;seethesidebarRPAScenarios).Theuseefficiencyofdifferentforestvegetationtypesinlocalamountofforestlandprojectedtoexperiencedroughtconditions,noranychangesinthatwateruseefficiencythatincreasesunderbothRCPs(figure5-14).By2050,thehot,couldresultfromshiftsinvegetationovertime.Therefore,dry,andmiddleclimateprojectionsproducemarkedincreasesactualexposurecouldvaryinwaysthatarenotcapturedinoverthehistoricalperiodinboththeextentandfrequencythisanalysis.ofdroughtacrosstheUnitedStatesunderbothRCPs.UnderRCP8.5andthehotanddryclimateprojections,morethanAhighlevelofdroughtexposuredoesnotnecessarily50percentoftheNation’sforestsareexposedtomoderate,translatetosignificantecologicalimpactsforaforesttypesevere,orextremedroughtinmostyearsafter2040.Wettergrouporforestedarea.Informationonexposurecanbeusedconditionsandlesswarmingresultinlowerpercentagesofinconjunctionwithresearchonthedroughtsensitivitiesofforestareaexposedtodroughtrelativetothehotanddryforesttypegroupsandassociatedtreespeciestodetermineprojections.Whilethemiddleclimateprojectionrepresentsthedegreeoflikelyecologicaleffectsfromdroughtandmoderatechangesintemperatureandprecipitationcomparedguidemanagementeffortstoamelioratetheseimpacts(seewiththeotherprojections,itstillprojectsmorefrequentthesidebarVulnerabilitytoDroughtforanexampleusingandwidespreaddroughtconditions,similartoresultsfromtheseSPEIdata).Forexample,recentseveredroughtsinthehotanddryprojections.Thisislikelytheresultofhighcombinationwithotherstressorsincludingherbivores,interannualvariationinprecipitationunderRCP4.5andwarmparasites,andwildfires,haveplayedaroleinwidespreadtreetemperaturesunderRCP8.5projectedbythemiddlemodel.mortalityandgrowthdeclinesinpinyon-juniperforests(FlakeandWeisberg2019a,2019b,Shawetal.2005),withhigherAnalysisofforestexposuretodroughtbyFIAforesttypemortalityoccurringonthedriestsitesaswellassiteswithgroup(figure5-15)providesinsightsintogeographicpatternsdeepersoilsandhigherstanddensity(FlakeandWeisbergofforestexposure.Wefocusonexposuretosevereorextreme2019a).Thissuggeststhatmanagementactions,suchasdroughtconditions(SPEI<-1.5)fora30-yearperiodinstandthinningtoreducetreedensity,mightbenecessarytothefuture(2041to2070,“mid-century”)andcomparethatincreasetheadaptivecapacityofpinyon-juniperforestsinexposuretoaperiodinthemodeleddataduringtherecentpastresponsetotheseimpacts(BradfordandBell2017).Onthe(1991to2020,“recentpast”).Thefuturedroughtexposureotherhand,thelongleaf/slashpinetypegroupthatoccursforseveralforesttypegroups,includingthreesmallertypeintheSoutheasternUnitedStatesisprojectedtofacelowtogroupsthatoccurinCalifornia—westernoak,Californiamoderatedroughtexposure,andatleastoneofitsdominantmixedconifer,andtanoak/laurel—maybesimilartothepastspecies(longleafpine,Pinuspalustris)islikelymoredrought-(figure5-15).However,projectionsunderbothRCPsusingtolerantthanothertreespecies(Samuelsonetal.2012,2019).someclimateprojectionsindicatelevelsofdroughtexposureThistypegroupmaythereforeberelativelyresilienttofuturethatfarexceedrecentexposureformanyforesttypegroups.droughtexposure,despiteaprojectedincreaseinexposureBymid-century,themedianprojectedexposuretosevereorbymid-century(figure5-15).ThelikelydroughtresilienceextremedroughtfortheclimateprojectionsunderRCP8.5oflongleafpinesisonereasonwhyrestorationofforestsinthepinyon/juniper,woodlandhardwoods,aspen/birch,intheSoutheasthasrecentlybeguntoemphasizecreatingandponderosapinetypegroupswasatleast60percent,farormaintainingaprominentlongleafpinecomponentasaexceedingthehistoricalexposuresforthosetypegroups.Forstrategyforclimateadaptation(Clarketal.2018b).theformerthreeofthosetypegroups,exposurewasprojected2020ResourcesPlanningActAssessment5-17Figure5-14.Proportionofforestlandareaincategoriesof36-monthSPEIforhistorical(1953to2005)andfuture(2006to2070)periodsusingtheRPAclimateprojectionsunderRCP4.5(top)andRCP8.5(bottom).TheperiodtotheleftofthedashedlineineachgraphindicatesthereferenceperiodthatwasusedtocalibrateSPEIvalues.RCP4.5RCP8.5SPEI>2,Extremelywet0.5<SPEI<1,Slightlywet-1.5<SPEI<-1,Moderatedrought1.5<SPEI<2,Severelywet-0.5<SPEI<0.5,Nearnormal-2<SPEI<-1.5,Severedrought1<SPEI<1.5,Moderatelywet-1<SPEI<-0.5,SlightlydrySPEI<-2,ExtremedroughtRCP=RepresentativeConcentrationPathway;SPEI=StandardizedPrecipitationEvapotranspirationIndex.Source:Costanzaetal.2022a.5-18FutureofAmerica’sForestsandRangelandsFigure5-15.ComparisonofmonthlyproportionofforesttypegroupsinsevereorextremedroughtforeachoftheRCPsatmid-century(2041to2070)withthesamemetricduringtherecentpast(1991to2020).DotsrepresentthemedianofthefiveRPAclimateprojectionsforthegiventimeperiod,andhorizontalbarsindicatetherangeofvaluesacrossthoseclimateprojections.Foresttypegroupsarearrangedaccordingtotheirarea(largestatthetoplefttosmallestatthebottomright;seefigure5-8forareasofforesttypegroups).RCP=RepresentativeConcentrationPathway.Exposureandsensitivityofforeststodroughtareonlyfactorstocharacterizewaterdeficitsthatresultinsubstantialonesetoffactorsindeterminingecologicaleffectsandimpactstoecosystemsandecosystemservices.Integratedresultingimpactsongoodsandservices.Droughtimpactstometricsofecologicaldroughtthatincorporatebothexposuretoforestsdependonanumberoffactors,includinglandscapedroughtandmeasuresofimpacttoforests,rangelands,andthecharacteristicssuchastheextentandconfigurationofecosystemservicestheyprovide(asinthesidebarVulnerabilityforestandotherlanduses,andpatternsofhumanactivitiestoDrought)canbeexpandednationwide.Approachesthatrelatedtowatersupplyanddemand,aswellasmanagementaccountforexpectedhumanpopulationandlanduseshifts(Crausbayetal.2017;alsoseetheWaterResourcesChapter).withinandamongU.S.regionscanhelpmitigatefuturedroughtForexample,evidencefromthe2011droughtineastTexasimpacts(WarziniackandBrown2019).Humanadaptationsshowsthatpines,andespeciallythoseinmanagedpinetodroughtsuchasgroundwaterminingcanhelpamelioratestandsthathadbeenthinned,hadlowerdroughtmortalityimpactsintheshortterm,butareineffectiveinthelongtermratesthanothergenera(Klockowetal.2020),suggestingthat(Brownetal.2019,USDAForestService2016).Additionaltreespeciesandmanagementbothaffectedforestdroughtresearchisneededregardingwaystomeetthewaterdemandsofimpacts.Recentemergingframeworksofecologicaldroughtcitiesandagriculturewhileensuringthatforestsaresufficientlyaimtointegrateacrosstheseecologicalandsocioeconomicdrought-resilientinthefaceofclimatechange.2020ResourcesPlanningActAssessment5-19VulnerabilitytoDrought:TheCaseStudyofTreeMortalityandRangelandProductivityinTexasThevulnerabilityofforestsandrangelandstodroughtviaSPEIchangedoverspaceandtimeforforestsanddependsontheirdegreeofexposure,sensitivitytodroughtrangelandsinTexas.conditions,andcapacitytoadapttothoseconditions(Crausbayetal.2017).WhileindividualspeciesandDistinctsignaturesofthedroughtcanbeseenineachoftheecosystemstowhichtheybelongcanhavedifferentthesevenregionsofTexas(figure5-16).Darkerbrownlevelsofdroughttolerance(ArchauxandWolters2006,areasrevealdrierconditions,bothinmagnitude(tallerBerdanierandClark2016,Brodricketal.2019,PetersontheYaxis)andduration(widerrangeontheXaxis).etal.2015),theimpactofaneventthatapproachesorBecauseofthe36-monthwindowusedwhencomputingexceedshistoricalextremesindurationormagnitudeSPEI,thesignaturesofthe2011droughtareevidentuntilcanbesubstantial,particularlyifitoccursoveralarge2014,eventhoughmoistureconditionsinTexasgenerallygeographicarea(Cliffordetal.2013,Schwantesetal.followedlong-termtrendsfromearly2012untilearly2017).Weillustratethiswithacasestudyofaperiodof2014(Fernandoetal.2016).AtcertainpointsduringtheexceptionaldroughtinTexas.signatureperiod,severeorextremedroughtconditions(SPEI<-1.5)extendedacrossatleast70percentoftheTexasandotherpartsoftheCentralUnitedStatesforestedareasineveryregion.Mostimportantly,theexperiencedoneoftheworstdroughtsonrecordin2011plotssuggestaconsistentrelationshipbetweentheSPEI,(Fernandoetal.2016,Grigg2014,Mooreetal.2016,ametricofdroughtexposure,andforestmortality(asNielsen-Gammon2012).Afterarelativelydrywinter,depictedbythestandingdeadtree/livetreeratio),ametricextremedroughtconditionsextendedthroughoutTexasofdroughtsensitivity.Therelationshipappearsstrongestduringthespringandsummerof2011,persistinginsomeinthenortheastandsoutheastregionsofTexas,whichpartsoftheStatethroughtheendoftheyear(Fernandohavethehighestforestdensity,andweakestinthewestetal.2016).Aheatwaveduringthesummerof2011region,whereforestissparselydistributed.Differencesexacerbatedthedrought(Hoerlingetal.2013)andwasbetweentheregionsintermsofforestmortality,suchasasecondarycontributortowidespreadforestmortality.whentheratiosofstandingdead/livetreesreachedtheirSimilarcompoundextremeeventscouldbecomemorepeakvalues,maybepartlyexplainedbydifferencesincommoninthefuture,highlightingtheimportancetheregions’predominanttreespecies,whichcanexhibitofunderstandingtheimpactofthiscompoundeventvariedmortalityratesbasedontheircapacitytosurviveonforestsandrangelands.AccordingtoFIAdata,androughtstressorassociateddisturbances,suchasdrought-estimated301milliontrees,morethan6percentoftriggeredpestoutbreaks(Klockowetal.2018).treesstatewide,werekilledbyacombinationofdroughtandhistoricallyhightemperatures(Hoerlingetal.Figure5-17showsthetemporalandspatialrelationships2013,Mooreetal.2016).Rainfallduringearly2012betweenmeteorologicaldroughtmeasuredvia6-monthimprovedmoistureconditionsacrossmuchofTexas,SPEIandrangelandproduction,anothermetricofdroughtbutextremedroughtlastedthroughout2012andintosensitivity,onabout69millionhaofrangelandinregions2013insomelocationselsewhereintheCentralUnitedofTexasforthe1984to2018period.ThereisanotableStates(Fernandoetal.2016,Tadesseetal.2015).InrelationshipbetweentheSPEIandproductiondataoverTexasalone,agriculturallossesfromthedroughtweretimeandbyregion.Duringdrierperiods,acorrespondingestimatedat$7.6billion(Fannin2012),exceedingthedecreaseinannualproductioncanbeseenintherangelandpreviousrecordof$4.1billionin2006.Ofthis$7.6productiontrend.Inmostregions,2011and2012showthebillion,livestocklosseswereestimatedat$3.2billion,longestandmostfar-reachingsustainedperiodofextremereflectingincreasedfeedingcostsandmarketlosses.drought(SPEI<-2)intherecord.Duringthattime,forageRangelandimpactswerefeltbeyondtheseeconomicconditionswerethesecondworstsince1984,exceptforeffects.ThedroughtresultedinforageyieldsfarbelowthenorthwestregionoftheState,whereforageconditionsanylevelsrecordedsince1984,thefirstyearofannualwerebyfartheworstonrecord.productionmeasuresfromtheRangelandProductionMonitoringService(Reevesetal.2020,2021).WeThesefiguressuggestthattheSPEIcanbeausefulmetricshowhowtwometricsofdroughtsensitivity—forestforexaminingforestandrangelandhealth.TheSPEIcantreemortalityandrangelandproduction—andtheiralsoinformmanagementactionstoincreaseadaptiverelationshipswithmeteorologicaldroughtmeasuredcapacityofforestsandrangelandstodrought,includingthinningandprescribedburninginforestsandremovalof5-20FutureofAmerica’sForestsandRangelandsFigure5-16.SPEIandtheratioofdead/livetreesbyregioninTexas,2004to2018.Foreachregion,thelinechartshowstheannualratioofstandingdeadtreestolivetrees,estimatedfromFIAdataandrepresentingforestmortality.Theplotbelowthelinechartshowsmeteorologicaldroughtasthemonthlyproportionoftheregion’sforestareaineachoftheSPEIcategories.Thenumberoflivetreesperhectareandareaofforest(FIAdatacirca2016)arelistedforeachregionbecausetheregionsdifferinforestareaanddensity.SPEI>21<SPEI<1.5-0.5<SPEI<0.5-1.5<SPEI<-1SPEI<-21.5<SPEI<20.5<SPEI<1-1<SPEI<-0.5-2<SPEI<-1.5SPEI36-monthFIA=ForestInventoryandAnalysis;SPEI=StandardizedPrecipitationEvapotranspirationIndex.Source:Costanzaetal.2022b.2020ResourcesPlanningActAssessment5-21treesorlargeshrubswhereencroachmenthasoccurredoneconomiclosses,willbecomemorefrequentintheserangelands.TheincidenceofdroughtsofthismagnituderegionsofTexasandelsewhere.Similaranalysesareanddurationareprojectedtoincreaseinthefuture(figuresneededforotherU.S.forestandrangelandecosystems5-14,5-21),suggestingthatsubstantialtreemortalityandtofurtherexplorerelationshipsbetweenexposureanddecreasesinrangelandproductivity,alongwithassociatedsensitivitytodrought.Figure5-17.SPEIandrangelandproductionbyregioninTexas,1984to2018.Foreachregion,thelinegraphshowsannualproductionobtainedfromtheRangelandProductionMonitoringService.Theplotbelowthelinechartshowsmeteorologicaldroughtasthemonthlyproportionoftheregion’srangelandarea(circa2011)ineachoftheSPEIcategories.SPEI>21<SPEI<1.5-0.5<SPEI<0.5-1.5<SPEI<-1SPEI<-21.5<SPEI<20.5<SPEI<1-1<SPEI<-0.5-2<SPEI<-1.5SPEI6-monthSources:RangelandProductionMonitoringService(Reevesetal.2020,2021);Costanzaetal.2022b;ReevesandMitchell(2011).5-22FutureofAmerica’sForestsandRangelandsRangelandsorshrubvegetation,whichrespondmorequicklytodroughtthanforestsintermsofbotheffectsandrecovery(FinchetRangelanddroughteffectsaresimilartoforestdroughtal.2016).effects.Ecologically,droughtresultsinreducedgrowthrates,defoliation,andincreasedstressonrangelandResultsfromSPEIanalysisfortheobservedhistoricalvegetation.Fromarangemanagementperspective,droughtperiodgenerallyconfirmknownintervalsofdroughtandgenerallyreducesthesupplyofwaterandassociatedforagerelativelywetconditions,bothacrosstheU.S.andwithinvegetation,whichcanleadtoreducedlivestockproduction,RPAregions(figure5-18).Majorrecentrangelanddroughtandinsomecasessubstantialeconomiclosses(Kelleyeteventsoccurredin2002intheRockyMountainRegion,al.2016).Additionally,becausemanyrangelanddroughts2011and2012intheSouthRegion,and2012through2016aredrivenbywarmtemperaturesthatlengthenthegrowinginthePacificCoastRegion.Ofthese,thedroughtsof2011season,thevegetationthatremainsduringdroughtscanand2012producedthegreatesteconomicimpactsintheexhibitincreasingdemandforwaterthroughincreasedrangelandsector(seethesidebarVulnerabilitytoDrought).evapotranspiration(UdallandOverpeck2017).RangelandEvaluatingdroughttrendsatnationalandregionallevelsdroughtshavebeenincreasinginfrequencyandseveritymayobscurehighlysignificanteventsoccurringatsub-overthelast50years,particularlyinthecentralGreatPlainsregionallevels.Forexample,althoughthesummaryofSPEIandSouthwest,andthetrendisexpectedtocontinue(CookacrosstheRockyMountainRegiondoesnotshowamarkedetal.2015).droughtsignalin2018,Coconino,Navajo,andApachecountiesinArizonahadsuchseveredroughtconditionsToassesscurrentandfutureexposureofrangelandsatthetimethattheyweredesignatedasnaturaldisastertodrought,weusedthe6-monthSPEI,ratherthantheareasbytheU.S.SecretaryofAgriculture(https://www.36-monthSPEIemployedforforests.Thisshorterperiodfsa.usda.gov/state-offices/Arizona/news-releases/2019/reflectsthefactthatrangelandsaredominatedbyherbaceousstnr_az_20190328_rel_01).CouplingnationalandregionalFigure5-18.Proportionofrangelandareaincategoriesofobserved6-monthSPEIovertime,basedonPRISMclimatedata,1953to2018.TheperiodtotheleftofthedashedlineineachgraphindicatesthereferenceperiodthatwasusedtocalibrateSPEIvalues.SPEI>2,Extremelywet0.5<SPEI<1,Slightlywet-1.5<SPEI<-1,Moderatedrought1.5<SPEI<2,Severelywet-0.5<SPEI<0.5,Nearnormal-2<SPEI<-1.5,Severedrought1<SPEI<1.5,Moderatelywet-1<SPEI<-0.5,SlightlydrySPEI<-2,ExtremedroughtSPEI=StandardizedPrecipitationEvapotranspirationIndex.Source:Costanzaetal.2022b.2020ResourcesPlanningActAssessment5-23analyseswithanalysisandmonitoringoflocaldroughtrangelands,particularlyduringtheperiodapproaching2070conditionsiscriticalfordeterminingdroughtextentandforunderbothRCPs.Asubstantialincreaseindroughtwasalsomoreaccurateaccountingofimpacts.projectedunderRCP8.5usingthemiddleclimateprojection.FutureprojectionsofdroughtshowthatthefrequencyofWeassessedtheprojectedfuturedroughtexposureofdroughtexposureisexpectedtoincreaseforrangelandsdominantrangelandvegetationtypes(figure5-20).WeacrosstheUnitedStates,underbothRCPsandallRPAsummarizedthemonthlyproportionofeachvegetationtypeclimateprojections(figure5-19),especiallybymid-centuryinsevereorextremedrought(SPEI<-1.5)forthesametime(2041to2070).Thehotanddryfuturesprojectedthemostperiodsassessedintheforesttypegroupanalysis(recentfrequent,widespread,andseveredroughtacrossU.S.past,mid-century).Overall,theanalysisshowsthepotentialFigure5-19.Proportionofrangelandareaincategoriesof6-monthSPEIforhistorical(1953to2005)andfuture(2006to2070)periodsusingtheRPAclimateprojectionsunderRCP4.5(top)andRCP8.5(bottom).TheperiodtotheleftofthedashedlineineachgraphindicatesthereferenceperiodthatwasusedtocalibrateSPEIvalues.RCP4.5RCP8.5SPEI>2,Extremelywet0.5<SPEI<1,Slightlywet-1.5<SPEI<-1,Moderatedrought1.5<SPEI<2,Severelywet-0.5<SPEI<0.5,Nearnormal-2<SPEI<-1.5,Severedrought1<SPEI<1.5,Moderatelywet-1<SPEI<-0.5,SlightlydrySPEI<-2,ExtremedroughtRCP=RepresentativeConcentrationPathway;SPEI=StandardizedPrecipitationEvapotranspirationIndex.Source:Costanzaetal.2022a.5-24FutureofAmerica’sForestsandRangelandsFigure5-20.EcologicalsubsectionsandtheirassociateddominantvegetationtypesforsummarizingSPEIprojections.SPEI=StandardizedPrecipitationEvapotranspirationIndex.Sources:EcologicalsubsectionsarefromClelandetal.(2007).VegetationtypesareEcologicalSystems(Comeretal.2003)thatweremappedin2012LANDFIREExistingVegetationTypedata(LANDFIRE2012).formuchhigherexposuretodroughtnearlyeverywherebyofRPAclimateprojections(leastwarm,hot,dry,wet,mid-century,withdifferingamountsofexposurebyvegetationmiddle)butalsothegeographicdistributionandextentoftype,andhigherexposuregenerallyunderRCP8.5(figuretherangelandsystem.Planningforadryorahotfuturemay5-21).Bymid-century,thevegetationtypeswiththehighestbeimportanttoaddressthepotentialrisktotheresourcesinlevelofexposureprojectedunderRCP8.5usingatleastonetheserangelandtypesatthelocalscale.climateprojectionincludethoselocatedintheSouthwesternUnitedStates,suchascreosotebushdesertscrub,grassland,Higherfutureexposuretosevereorextremedroughtnearlyandgrasslandandsteppe.Eachofthosetypesiscommoneverywhere,especiallyinthearidSouthwesternUnitedinArizonaandNewMexico,andtheformertwoarealsoStatessuggeststhatthewaterresourcesalreadyscarceinthatpresentinsouthernCalifornia(figure5-21).Acomparisonofregioncouldbefurtherstrainedbytheendoftheprojectionthemedianexposuresforthetwotimeperiodsindicatesthatperiod,havingimpactsonecosystemgoodsandservicestheseandothervegetationtypesoccupyingthearidregionsof(seetheWaterResourcesChapter).AlteredtimingofpeaktheSouthwestareexpectedtoexperienceafour-tofive-foldflowsandshiftsfromperennialtomoreintermittentflow,(RCP4.5)orsix-toeight-fold(RCP8.5)increaseinexposureespeciallyinstreamsintheSouthwest(GutzlerandRobbinstosevereorextremedroughtconditionsbymid-century2011,Zipperetal.2021)mayfurthercomplicatethetiming(figure5-21).Theincreaseseenhereissimilartoresultsfromandamountofwateravailability.Forageresourceswouldotherrecentresearchshowingthepotentialforunprecedentedlikelybecomesparseundertheseconditions,suggestingdroughtintheSouthwesternUnitedStatestowardthethatsignificantreductionsinthedensityofnativeandlatterhalfofthiscentury(Cooketal.2015),andageneraldomesticungulatesmaybenecessary(Fordetal.2019,agreementamongclimatemodelsthatdroughtexposurewillReevesetal.2017).Inaddition,theexpansionofinvasiveincreaseinalready-dryregionsoftheWest(Bradfordetal.speciessuchasredbrome(Bromusrubens)andLehmans2020).Inadditiontothosethreesouthwesterntypes,medianlovegrass(Eragrostislehmanniana)maybeenhancedprojectionsforothervegetationtypesthathavehadmoderateifnativeperennialsandannualsundergomorestressdroughtexposureintherecentpast,shortgrassprairieandrelatedtosoilmoisturedeficits(CurtisandBradley2015).sandshrublandindicateevengreaterchangesinexposureratesProjectionresultsforallrangelandvegetationtypesshowbymid-century.Six-toseven-fold(RCP4.5)or10-fold(RCPthepossibilityofworseningexposuretosevereorextreme8.5)increasesinexposuretosevereorextremedroughtaredroughtunderbothRCPsbymid-centurycomparedwiththeprojectedforthosetypesbymid-century(figure5-21).earlycenturytimeperiod,suggestingtheimportanceoftimelyimplementationofmanagementormitigationactionstoenableBymid-century,theprojectedrangeofdroughtexposureadaptationthatisrobusttoworseningdrought(seetheWaterforeachrangelandtypereflectsnotonlythewideselectionResourcesChapterforexamples).2020ResourcesPlanningActAssessment5-25Figure5-21.ComparisonofmonthlyproportionofrangelandecosystemsinsevereorextremedroughtforeachoftheRCPsatmid-century(2041to2070)withthesamemetricduringtherecentpast(1991to2020).DotsrepresentthemedianofthefiveRPAclimateprojectionsforthegiventimeperiod,andhorizontalbarsindicatetherangeofvaluesacrossthoseclimateprojections.Seefigure5-20foramapoftheserangelandsystems.RCP=RepresentativeConcentrationPathway.5-26FutureofAmerica’sForestsandRangelandsNonnativeInvasivePlantsininvasiveplantspecies(Oswaltetal.2015),definedasForestsandRangelandsthoseofanygrowthformlikelytocauseeconomicorenvironmentalharm(Riesetal.2004).Anationalanalysisof❖ThehighestratesofforestinvasionhaveoccurredFIAplotdataacrosstheUnitedStates(includingAlaskaandHawaii)from2005to2018revealedastrongdifferentiationthroughouttheRPASouthRegionaswellasininthepercentofinvadedplotsbetweencountiesintheEastmetropolitanareasandagriculture-dominatedandWest(figure5-22).CountiesthroughoutmuchofthecountiesintheRPANorthRegion.RPASouthRegionandthemid-AtlanticandMidwesternStatesoftheRPANorthRegionhadthehighestpercent❖Foresttypegroupsinthoseregionshadtheofinvadedplots,withlowerlevelsofinvasioninpartsofthesouthernAppalachians,thesoutheasternCoastalPlain,highestratesofinvasion,especiallywhereforestnorthernFlorida,andtheGreatLakesStates.Theseresultswasprivatelyowned.likelyunderestimatetheoverallpresenceofinvasiveplantspeciesbecausefieldcrewsonlyrecordspeciesthathavebeen❖Futureincreasesindevelopedoragriculturallandidentifiedpreviouslyasproblematic.ThegeographicpatternsareconsistentwithrecentworkthatalsodetectedthehighestuseintheEasternUnitedStatescouldleadtoprevalenceofforestplantinvasionintheSoutheast,inthehigherforestinvasionrates.agriculturally-dominatedMidwest,andnearmetropolitanareas(Iannoneetal.2015).Theseresultsfurtherunderscore❖CountiesintheRPAPacificCoastRegionhadthethefindingthateasternFIAplotsaremostlikelytobeinvadedinrelativelymoreproductive,fragmentedforestininterfacehighestratesofrangelandinvasion,specificallyinlandscapescontainingmorethan10percentagricultureorcoastalandsouthernCalifornia.developedlandcover(Riittersetal.2017;alsoseetheLandResourcesChapter).ForestsWeusedFIAdatatoestimatetheforestareathathasbeenNonnativeinvasiveplantspeciescauselong-termdetrimentalinvadedbynonnativeplantspeciesnationally,withinRPAeffectsonforestecosystems,includingdeclinesinbiologicalregions,andbyownershipwithinmajorforesttypegroupsdiversity,alterationstoforestsuccession,andchangesin(RiittersandPotter2019).Nationally,approximately62.7nutrient,carbon,andwatercycles(Liebholdetal.2017,millionhaofforestwereinvaded(36.2percentoftheforestMacketal.2000,Martinetal.2009).Thedamagecausedinventoriedforinvasiveplants,figure5-23).Forestlandbytheseinvasivespecies,andtheeffortstocontrolthem,areintheSouthRegionhadthehighestproportionofinvadedcostly(Pimenteletal.2005),evenbeforeaccountingfortheforestarea(57.7percentofinventoriedarea,52.7millionimpactstononmarketeconomicservicessuchasrecreationha),followedbytheNorthRegion(54.5percent).Theandlandscapeaesthetics(Holmesetal.2009).TheForestforestareainthetwowesternregionswasconsiderablylessInventoryandAnalysis(FIA)programcollectsinvasiveinvaded(7.5percentintheRockyMountainRegionand5.0plantdatabasedonexpert-derivedlistsofproblematicpercentinthePacificCoastRegion).TheseproportionsandareasofinvadedforestarelikelysubstantialunderestimatesFigure5-22.PercentofFIAforestplotsinvadedbycounty.Countieswithbecauseonly61percentofallforestwasinventoriedforfewerthanfiveplotsthatweresurveyedforinvasiveplantswereomittedandinvasiveplants,withmuchsmallerpercentagesinventoriedareshowningray.intheNorthandPacificCoastRegions.FIA=ForestInventoryandAnalysis.Forthemostinvaded,commonlyoccurringforesttypeSource:PotterandRiitters2023.groups,suchasoak/hickory,loblolly/shortleafpine,oak/pine,andoak/gum/cypress,thelargemajorityofinvadedforestwasinprivateownership(figure5-23).ThelargeproportionofinvadedforestinprivateownershipagreeswithpreviousresearchshowingthatprivatelyownedforestlandsintheEasternUnitedStateshadthehighestratesofinvasion(Riittersetal.2018),likelybecausetheyareclosertohumanlanduses,whichcontributeseedsourcesthatareresponsibleforplantinvasions.Aslandusechanges,futureprojectedincreasesinforestareacontainedwithintheWUI(seethesidebarWildland-UrbanInterfaceintheLandResourcesChapter)orexposed2020ResourcesPlanningActAssessment5-27Figure5-23.Areaofforestinvadedandnotinvaded,byownershipwithinFIAnonnatives(Reidetal.2009).Theseresultsadduptoafutureforesttypegroups.Thenumbersattheendofeachbarindicatethepercentofinwhichinvasionratesarelikelytoincreaseonforestland.forestwithineachtypegroupthatwassurveyedforinvasiveplants.Barstotheleftofthe0lineindicateinvaded;barstotherightindicatenotinvaded.WhilethesesummariesofinvadedforestareasdonotdirectlyaddresstheecologicaloreconomicimpactstoFIA=ForestInventoryandAnalysis.forests,someimpactstoforestsarelikelybecausetheinvasivespeciessurveyedbyFIAareconsideredproblematictonearbyagricultureanddevelopment(seethesection(Oswaltetal.2015).InformationaboutforestinvasionratesProjectedForestFragmentationandLandscapeContextandimpactsislikelytoimproveasatemporalrecordofdataintheLandResourcesChapter)willlikelyincreaseseedfrominvasiveplantsurveysatbroadscalesisaccumulatedsourcesandthusincreaseinvasionratesinforestland.RoadandifFIAexpandsinvasiveplantinventoriestoincludeconstructionissimilarlyexpectedtoincreaseratesofforestforestlandthathasnotyetbeensurveyedforinvasiveplantsplantinvasionsinnearbyforests(FormanandAlexander(Oswaltetal.2021).1998).Whileprivatelyownedforestlandhadhigherratesofinvasionthanpublicland,theproximityofprivatelandtoRangelandshumanlanduses,ratherthanownershipperse,islikelytheunderlyingfactorresponsibleforthedifference.Therefore,Nonnativeinvasiveplantspeciescancausewholesalechangesinownershiporprotectionstatusaloneareunlikelychangestotheecologicalandeconomichealthofrangelandtopreventfutureinvasions(Riittersetal.2018).Inadditionecosystems.Manyrangelandsthatweredominatedbytolandusechange,widespreadintercontinentalmovementperennialbunchgrasseshavebeeninvadedbynonnativeofplantsforornamentalpurposesisalmostcertaintoensureannualgrasses,whichincreasewaterdemand;causemorefutureintroductionsofnewnonnativeinvasiveplantsintofrequent,higherseverity,largerfires;lowerlivestockyieldsforests(TheoharidesandDukes2007).Onceforestlandisandforagequantity;andleadtosubstantialeconomiclossesinvaded,itisunlikelytobecomeun-invadedinmostfuture(DiTomaso2000,Rottleretal.2015).Noconsistentnationalcircumstances,giventhatmanagementofinvasiveplantinvasivespeciesrangelandinventoryisavailablethatcoversspeciesinforestsoftenresultsintheirreplacementbyotherallpublicandprivatelands.Hence,weuseddatafromtheCenterforInvasiveSpeciesandEcosystemHealthattheUniversityofGeorgia(theBugwoodProgram,www.Bugwood.org)toinvestigatenonnativeplantsincountiescontainingsubstantialrangelandarea(exceeding60,703ha,basedonReevesandMitchell2011;seefigure5-1forthedistributionofrangeland).DatafortheBugwoodProgramisusuallycollectedbyvolunteersrecordinglocationsofnonnativespeciesandthusmaybebiasedtowardhighercountsinpopulousareasorcountieswithmorepublicland(Wallace2020).Thenumberofnonnativeplantspeciesinrangelandcountiesgenerallyincreasedfromeasttowest,peakingincoastalCalifornia(figure5-24).SanDiego,LosAngeles,andMarincountiesarereportedtohost579,566,and494nonnativespecies,respectively.CountiesintheRPAPacificCoastRegioncontainedthehighestnumbersofnonnativespecies,followedbycountiesinthewesternportionoftheRockyMountainRegion.ThelowestnumbersofnonnativespecieswereexhibitedbygrasslandareasoftheGreatPlains,includingtheeasternportionoftheRockyMountainRegionaswellaspartsofOklahomaandTexasintheSouthRegion.AfewcountiesintheNorthRegionhadenoughrangelandareatobeincludedinthisanalysisbutwereinsufficientfordiscerningageographicpattern.Whenthenumberofnonnativespeciesineachcountywasstandardizedbytheareaofrangelandinthecounty(“density”ofnonnativespecies;figure5-24),thegeographicpatternwasslightlydifferent.Similartotheresultfortheoverallnumberofnonnativespecies,theRPAPacificCoastRegionhadthe5-28FutureofAmerica’sForestsandRangelandsFigure5-24.Totalnumber(top)anddensity(bottom)ofnonnativeplantGreatPlainscouldreflectgreaterresistancetoinvasioninspeciesinrangelandcounties.Rangelandcountiesaredefinedasthosethatsomerangelandecosystems.Anemergingframeworkthatcontainmorethan60,703haofrangeland(ReevesandMitchell2011).Seesummarizestherangelandecosystemattributesandlandscapefigure5-1fordistributionofrangeland.characteristicsthataffectresiliencetoplantinvasionandresultingwildfire(Chambersetal.2014,2019)couldbe03807601,520NumberofincorporatedinfutureRPAAssessmentstoprovidefurtherkminvasivespeciesinsightsintoinvasionpatterns.0–28Giventhepotentialbiasesinthedatatowardhighercounts29–44onpubliclands,cautionisrecommendedforinterpretation45–71oftheseresults.Forexample,manycountiesinTexasshow72–119relativelylownumbersofnonnativespecies,butrangeland120–200countiesintheStateexhibitapproximately98percent201–340privatelandownership,andsomeprivatelandownersmightbereluctanttomakedataabouttheirlandwidely¯341–579accessible.Inaddition,becausethesedatadocumentevenindividualoccurrencesofanonnativeplantspeciesinaNumberofgivencounty,theydonotnecessarilyrepresentgeographicnonnativespeciespatternsofecologicaloreconomicimpact.Whiledatacollectioneffortsinseveralagenciesdocoversuchper10,000haoccurrences,includingtheNationalResourcesInventoryofrangelandoftheUSDANaturalResourcesConservationServiceandtheAssessment,Inventory,andMonitoringStrategyofthe0.00–0.02U.S.BureauofLandManagement,obtainingthosedatainrangelandcountiesischallengingduetoprivacyconcerns.0.03Nonetheless,usingthosedatasetsintandemcouldimprovetheassessmentofinvasiveplantdistributionsinrangelands,0.04–0.05improveunderstandingoftheirimpacts,andenablefutureprojectionsoftheirspread.0.06–0.09InsectandDiseaseDisturbances¯03807600.10–0.19inForests1,5200.20–0.40❖Theoverallareaofforesttreecanopymortalitykm0.41–0.87causedbyinsectsanddiseaseswasusually¯Source:CenterforInvasiveSpeciesandEcosystemHealthattheUniversityofGeorgia(theBugwoodhigherintheRPARockyMountainandPacific03h8a0=he7c6t0ares.1,520CoastRegionsthanintheSouthandNorthkmRegions.Program,www.Bugwood.org).❖Nonnativeinsectsanddiseaseshadalargergreatestdensityofnonnativeplantspecies,withthehighesteffectonforestmortalityintheNorthRegionthandensitiesincountiesinandaroundtheCaliforniabayareainotherregions.andalongtheCaliforniacoast.Unliketheoverallgeographicpatternfornumberofnonnativespeciespercounty,the❖DefoliationwasmorewidespreadintheNorthandgeographicpatternofnonnativespeciesdensitydidnotincreasegenerallyfromeasttowest.ScatteredcountiesinSouthRegionsthaninthetwowesternregions.centralUtah,theupperSnakeRiverPlain,andineasternKansasalsohadhighdensitiesofnonnativespecies.❖Thefutureeffectsofinsectsanddiseasesin0Thelargenumbersof¯nonnativeplantspeciesinmanyforestsareuncertain,butmostfactorsassociated3807601,520havearelativewithawarmerclimatecontributetoagreaterwesterncountieksmmaysuggestthatrangelandspotentialforoutbreaks.lackofresistancetoinvasion.ResearchinmanyrangelandInsectsanddiseases,especiallynonnativeinvasiveagents,havethecapacitytocauseecologicalandeconomicdamageecosystemshasdemonstratedaninvasivegrass-firecycle,toforests(Lovettetal.2016,Tobin2015).Individualinsectsanddiseaseshaveextirpatedentiretreespeciesorgenerawhereinlonger,morefavorablegrowingconditions,andfundamentallyalteredforestsacrossbroadregions.Forexample,chestnutblight,acankerdiseasecausedbytheinappropriategrazingregimes,andalteredfireregimescanallownonnativeannualgrassestosurvive(D’AntonioandVitousek1992,Fuscoetal.2019).Thosegrassessubsequentlyalterthemoistureandfireregimes,creatingnewenvironmentsthatfavorevengreaterrichnessandabundanceofnonnativeannualgrassspecies(Roundyetal.2018).Ontheotherhand,thelownumbersofnonnativeplantspeciesinpartsofthe2020ResourcesPlanningActAssessment5-29introducedfungusCryphonectriaparasitica,functionallytheNorthRegionduringthe2002to2006periodbecauseeliminatedtheAmericanchestnutfromitsrangeacrosssurveyorsdrewpolygonstoencompasslargeareasaffectedtheEasternUnitedStates(Loo2009).Thiseliminationbydispersedemeraldashborerandbalsamwoollyadelgidprocessisnowbeingrepeatedforseveralashspeciesin(Adelgespiceae)infestations,ratherthandefiningonlythetheUnitedStatesandCanadabytheemeraldashboreraffectedareasaswasdoneinotherregions.Documented(Agrilusplanipennis),aninsectintroducedfromnortheasternmortalityhasgenerallybeenmuchmorewidespreadAsia(Kloosteretal.2018).Trackinginsectanddiseasefrominsectsthandiseases,withbarkbeetlesconsistentlyinfestationsovertimeisnecessarytounderstandtheextentreportedasthemostimportantmortalityagentsacrossallanddurationoftheirimpactsonforestecosystemstructure,regionsandovertime,particularlyintheWest(Potteretal.function,anddynamics.TwentyyearsofInsectandDisease2020).Mountainpinebeetle(Dendroctonusponderosae)Survey(IDS)data,collectedannuallybytheForestHealthwasresponsibleforamortalitypeakintheRockyProtectionprogramoftheU.S.DepartmentofAgriculture,MountainRegionfrom2007to2011,whilefirengraverForestService(FHP2019),enabletrenddetectionover(Scolytusventralis)andwesternpinebeetle(Dendroctonustimeforinsectanddiseasedamage(Potteretal.2020).brevicomis)causedincreasedmortalityinthePacificCoastWesummarizedtheforestareainwhichtreecanopywasRegionfrom2012to2016.affectedbyinsectsordiseasesnationally(includingAlaskaandHawaii)andwithinRPAregionsinfour5-yeartimeNonnativeinvasiveinsectsanddiseaseshadalargerrelativewindows(1997to2001,2002to2006,2007to2011,contributiontoforestmortalityintheNorthRegionthanand2012to2016)tohighlightplaceswhereforestswereelsewhereintheUnitedStates(figure5-26).Thelistofsuchimpactedbyinsectordiseaseagents.speciesintheNorthRegionislengthy,includingemeraldashborer,hemlockwoollyadelgid(Adelgestsugae),balsamThetreecanopyareaaffectedbynativeandnonnativewoollyadelgid,beechbarkdisease(causedbytheinsectmortality-causingagentshasbeenconsistentlylargeacrossCryptococcusfagisugaandassociatedNeonectriafungus),thethreemostrecent5-yearassessmentperiods.TheRPAandoakwilt(causedbythefungusBretziellafagacearum).NorthRegionexperienceditsgreatestaffectedareain2002Nonnativeinvasiveagentshadsubstantialimpactselsewhereto2006,thePacificCoastRegion(whichhereincludesaswell,includingHawaii,whererapidʻōhiʻadeath,afungalAlaskaandHawaii)in2002to2006and2012to2016,diseasecausedbyCeratocystishuliohiaandC.lukuohia,andtheRockyMountainRegionin2007to2011and2002iscausingconsiderablemortalitytooneoftheState’smostto2006,whiletheSouthhadcomparativelylimitedareaecologicallyandculturallyimportanttreespecies(Fortiniwithmortality(figure5-25).Forestmortalityfrominsectsetal.2019).Elsewhere,andespeciallyintheWest,nativeanddiseasesmaybeunderrepresentedintheSouthRegionagentsincludingthewesternpinebeetlementionedabovebecauseofthemoreintensemanagementcyclesincludinghavebeenconsistentlyimportantcausesofmortality.rapidremovalofaffectedtrees,andhighergrowthanddecayratesleadingtomorerapidforestrecoveryafterWhiletreecanopymortalityisonecriticaleffectofinsectsdisturbance.Forestmortalityislikelyoverrepresentedinanddiseases,someagentsalsocausesubstantialdamageviadefoliation.ThetreecanopyareaaffectedbydefoliationFigure5-25.Areaofmortalityattributedtobothinsectanddiseaseagentsinagentshasremainedrelativelyconsistentovertimeandhas5-yearintervals,byRPAregion(AlaskaandHawaiiareincludedinthePacificusuallyequaledorexceededtheareaaffectedbymortalityCoastRegion).agents,withnonnativedefoliatorsmoresignificantintheRPANorthRegion(includingEuropeangypsymoth,1997–20012002–20062007–20112012–2016Lymantriadispar;larchcasebearer,Coleophoralaricella;andwintermoth,Operophterabrumata)andSouthRegion(Europeangypsymoth)comparedtothewesternregions(Potteretal.2020).Thisevaluationofrecentmortalityanddefoliationfrominsectsanddiseasesprovidescontextformanagersabouttheimplicationsandscopeofcurrentforesthealththreatsatanationalscale.Knowinghowthesetrendswillchangeinthefuturecanprovidecriticalinformationforlandmanagementplanninganddecisionmaking.Thefutureimpactsofforestinsectsanddiseasesarehighlyuncertain,compoundinguncertaintyaboutclimatechangewithuncertaintyabouttheeffectsofclimaticconditionsoninsectsanddiseases,aswellasonthedistributionoftreehostspecies,andaboutwhatnewSource:InsectandDiseaseSurvey(IDS)data(FHP2019).5-30FutureofAmerica’sForestsandRangelandsFigure5-26.Theproportionofmortalityattributedtononnativeinvasiveagentsversusnativeagentsandthosewithunknownoriginin5-yearintervals,byRPAregion(AlaskaandHawaiiareincludedinthePacificCoastRegion).Source:InsectandDiseaseSurvey(IDS)data(FHP2019).invasiveagentswillbeintroducedintotheUnitedStates.conditionsmayincreasethefrequencyandseverityofSpecifically,predictingtheconsequencesofclimatechangestormsthatresultinfallenorbrokentreesthattriggerbarkontheforesthealthimpactsofpestsisdifficultgiventhebeetleoutbreaks(Marinietal.2017,Raffaetal.2015).Atcomplexrelationshipsamongabioticstressors,hosttrees,thesametime,otherfactorsrelatedtochangingclimaticinsectherbivores,andthenaturalpredatorsandparasitoidsconditionsmaycounteractthepotentialforincreasedfutureofthoseinsects(Jacteletal.2019).Severalfactorssuggestpestoutbreaks.Forexample,forestinsectdevelopmentalanincreasedpotentialforinsectanddiseaseoutbreaksratesdecreaserapidlybetweenanoptimaltemperatureinthefuture.Forexample,itispossiblethatwarmerandahotlethalthreshold(DavídkováandDoležal2019),temperaturesmayresultinhighernumbersofbroodssowarmingconditionscouldresultinincreasedinsectwithinayearforsomeinsects,resultinginpopulationmortality(Mechetal.2018).Highertemperaturesmayalsooutbreaks(Bentzetal.2019),andallowinsectherbivoresresultinsmallersizeandlowerdispersalcapacityofnewlytoexpandtheirrangesintoareasthatwerepreviouslytooemergedadultinsects(Pineauetal.2017),whilevariabilitycold(Dukesetal.2009).Thelocalexpansionoftherangesintemperaturescouldreduceforestinsectsurvival(Davidofsomeinsectsanddiseasesduetoclimatechangehasetal.2017).IncreasedCO2mayalsonegativelyimpactalreadycausedforestmortalityandpresentschallengesforforestinsectperformance,althoughthiscouldbeoffsetbymanagement(seethesidebarSouthernPineBeetleRecentelevatedtemperatures(ZverevaandKozlov2006).ClimateRangeExpansionforasummaryandexample).Inaddition,changemayalsoaffectrelationshipsbetweenforestinsectsclimatemodelprojectionspointtomoredroughtunderandtheirpredatorandparasitoidenemies,althoughhowsomeplausiblefutures(seethesectionDroughtinForeststheserelationshipschangeislikelytobecomplicatedbyandRangelands).Droughtsmaybenefitforestinsectpestsseveralfactors(JeffsandLewis2013).Changingclimatebyreducingtreeresistance,withbarkbeetles,sapfeeders,conditionsaregenerallyexpectedtobenefitforestpests,butandleafchewersmorelikelythanotherinsectguildstonegativeeffectsofwarmingmaymitigatetheirimpactsonbenefitfromdrierconditions(Jacteletal.2012),althoughforesthealthinsomecircumstances(Jacteletal.2019)whilethedegreeofdroughtstressaffectshowwelltreesresistinteractionsamongdisturbancescouldproducefeedbacksbarkbeetles(Raffaetal.2008).Finally,changingclimatethatpreventworst-caseoutcomes(Lucashetal.2018).2020ResourcesPlanningActAssessment5-31SouthernPineBeetleRecentRangeExpansionintoNewJerseyandNewYorkClimatechangehasalreadyenabledthespreadofsomepitchpinebarrensofLongIsland,anareawhereithadnotnativeforestinsectsanddiseasesintoareasoutsidetheirbeenpreviouslyrecorded(Heussetal.2019).Pitchpinehistoricalranges(Doddsetal.2018,Heussetal.2019,hasbeennearlyeliminatedfromaffectedsites,whichhaveWeedetal.2013).Inmanyoftheseinstances,warmershiftedtowardhardwooddominanceasaresult.Effortswintertemperatureshavereducedorremovedcold-tosuppresstheinfestationshavealsoledtoaccumulationtemperaturerestrictionsthatpreviouslykeptpopulationsofdownedwoodydebris,increasingfirerisk(Heussetincheck(Kolbetal.2016,Lesketal.2017).Suchrangeal.2019).Thebeetlehassincebeencapturedintrapsinshiftsgivepestsaccesstonovel,nonadaptedhostspeciesConnecticut,RhodeIsland,andMassachusetts(Doddsorareasthatpreviouslywereonlymarginallysuitableetal.2018),raisingconcernsthatclimate-drivenrangeforapest,andcanthereforehavenotableecologicalexpansioncouldallowittoexploitotherpotentialhostsandeconomicconsequencesforforests.Ecologicalsuchasredpine(P.resinosa)andjackpine(P.banksiana).consequencescanincludedirectimpactstotreesintermsThisexpansionofsouthernpinebeetle,andsimilarrangeofmortalityorstress,aswellasdisruptionofexistingexpansionsbyotherforestinsectsanddiseases,presentsdisturbanceregimesandincreasedsusceptibilitytoachallengetomanagers,whomayhavetoadapttheirrelatedforesthealththreatssuchaswildfiresanddroughtmethodstoapossiblyunfamiliarpestbasedonknowledge(Andereggetal.2015,Pureswaranetal.2018).Economicacquiredinothergeographicsettings,whichmaynotconsequencesincludemitigationcostsaswellasdirecttranslatewelltotheircircumstances(Weedetal.2013).economiclossesfromtreemortality(Heussetal.2019,Kolbetal.2016,Weedetal.2013).Figure5-27.ForestmortalitycausedbysouthernpinebeetleinNewYorkandNewJerseyfrom1999to2017.Thesouthernpinebeetle(Dendroctonusfrontalis)isthemosteconomicallysignificantforestpestintheSource:InsectandDiseaseSurveydata(FHP2019).SoutheasternUnitedStates.Priortothe2000s,mostoutbreaksofthebeetleoccurredinaregionextendingfromTexastoVirginia,althoughinfestationswereinfrequentlyreportedasfarnorthasPennsylvaniaandsouthernNewJersey(Doddsetal.2018).Outbreakswerehistoricallymostcommoninforestsdominatedbyloblolly(Pinustaeda)andshortleaf(P.echinata)pines.Since2001,southernpinebeetleoutbreakshavefollowedasteadynorthwardprogressionintoforestsdominatedinsteadbypitchpine(P.rigida);thisexpansioncoincideswithadocumentedwarmingtrend(Doddsetal.2018,Lesketal.2017).InsectandDiseaseSurvey(IDS)datashowareasofforestmortalitycausedbythesouthernpinebeetleinNewJerseyandNewYorkfrom1999to2017(figure5-27).GradualnorthwardadvancementofmortalityisevidentinsouthernNewJersey,andbythe2015to2017period,thebeetlewaswidespreadinthe5-32FutureofAmerica’sForestsandRangelandsForestRemovalAreasItisimportanttobenchmarktheseresultsagainsttheareaofannualremovalsestimatedfromground-basedforestinventories❖Whileremovalshavewide-rangingeffectsforsimilarperiods.ReportsbasedonFIAdatashowconsistentnationalaverageremovalratesof4.5millionhayr-1,acrossonforests,removalsareanimportantforestmultipledecades(althoughthisestimateincludes0.35millionmanagementtoolforpreventingormitigatinghareportedinAlaska)(BirdseyandLewis2002,Oswaltetal.impactsfromnaturaldisturbances.2014,Smithetal.2009).Whileforestinventorydatacanhaveamoreinclusivedefinitionofremovals,opticalsatelliteimagers❖TheannualareaofforestcanopylossfromlikeLandsatcanonlydetectremovalsthatresultinoverstorytreecanopyloss,andarelessaccuratewhenlessthan20percentremovalsintheUnitedStatesaveraged2.44ofcanopycoverhasbeenremoved(Cohenetal.2016,Zhaoetmillionhabetween1986and2010,with65al.2018).percentofthetotaloccurringintheRPASouthRegion.Theobservedtrendsinremovalareascorrespondwithknowntrendsinpolicyandmarkets.First,thepeakremovalrateandRemovalsaretreestakenoutofforestsduringtimbersubsequentdecreaseobservedfrom1988to1990intheRPAharvestingorotherculturaltreatments,orduetoland-usePacificCoastRegioncorrespondstodocumentedshiftsofchange.Likeothertypesofdisturbances,removalscanhaveregionaltimbersalesduetoendangeredspottedowlhabitatwide-rangingeffectsonforestsandtheirassociatedgoodsandrestrictions(Huangetal.2012,WearandMurray2004).services.RemovalscannegativelyaffectforestcommunitySecond,recordlumberconsumptionfrom2003to2005,highassembly,structureandfunction,andproductivity(Dunckerlevelsofhousingstartsin2005,andthesubsequentcrashinetal.2012,Falletal.2004,Jacteletal.2009);carbonstoragehousingpricesandlumbermarketsduringtheglobalfinancial(Birdseyetal.2006);waterandsoilquantityandqualitycrisisof2007to2009correspondtothetiminganddirections(BirdseyandLewis2002,Naveetal.2010,Yanaietal.2003);ofremovaltrendsacrossallregions(InceandNepalandwildlifehabitatandbiodiversity(Verschuyletal.2011).2012,Woodalletal.2012).Third,thetimingofthepeakRemovalstodecreaseforeststanddensities,however,canserveremovalrateintheSouthRegionoccurringaround1997totopreventormitigateimpactsfromotherdisturbancessuchas1998correspondstoregionaltrendsinvolumeremovalforfireorinsectanddiseaseoutbreaks(Fettigetal.2014,Leverkusroundwoodproduction(Smithetal.2009,WearandGreisetal.2018,LindenmayerandNoss2006,Masonetal.2006),2013).Fourth,allregionsshowsteepincreasesinremovalhelpsomeforestsadapttoincreasingwaterstress(Botteroetratesatthebeginningoftherecord.DatafromFIAalsoshowal.2017,BradfordandBell2017),increaseproductivityforasteepincreaseintheSouth’sannualvolumeremovalratetimbermanagement(D’Amatoetal.2011,Fox2000),andovertheperiod1986to1997(Smithetal.2009),andallprovidecriticalearly-successionhabitatforwildlifespeciesregionshadanincreaseinlumbervolumesupplyduringthatintheabsenceofotherdisturbances(KingandSchlossbergtime(WearandMurray2004).2014).Removalscanbedirectlyandimmediatelyinfluencedbypolicy,economicincentives,andmanagementgoals(CubbageWereportsummariesofremovalsintermsofareabecauseandNewman2006,Ellefsonetal.2006,Legaardetal.2015),theremotesensingproductsweusedfocusonareaestimates.unlikemanyotherdisturbanceprocesses(butseethesidebarOthersources,includingreportingbasedonFIA,haveEffectsofAirPollutiononForestEcosystemsforanexceptionsummarizedremovalsintermsofvolumeestimates(SmithinwhichtheCleanAirActhashadsubstantialeffectsonacidetal.2009;seetheForestResourcesChapterforvolume-deposition).Characterizingthespatialandtemporalpatternsofbasedreporting).Itisthereforeusefultounderstandtheremovalregimesisanimportantcomponentofunderstandingrelationshipbetweenvolumeandareaofremovals,whichsustainabilityinlightofdisturbanceinteractionsandclimatedependsonthreefactors:(1)theharvestintensity(i.e.,volumechange(Kurzetal.1998,Leverkusetal.2018,Seidletal.2008).perunitareaharvested);(2)thenaturalormanagedtimberproductivityoftheland(volumeavailableperunitarea);andAnnualareasofforestremoval,measuredhereintermsofthe(3)howvariabletheharvestintensityisacrosstimeandspace.areaofforestcanopylossfromremovalseachyear,werederivedWhiletotalregionalproductivityisrelativelystableovertime,fromatimeseriesofLandsatsatelliteimageryfortheperiodFIAdatahaveshownthatharvestintensityvariesconsiderably1986to2010(Schleeweisetal.2020)(figure5-28).Nationally,acrossandwithinregions(Maseketal.2011,Schleeweisetal.removalsoccurredatameanannualrateof2.44millionha2013).Inlowerproductivityareas,whereittakesmoreforest(roughly1percentoftotalforestperyear)andrangedbetweenareatoreachacertainvolumeofremoval,adecreaseinlow-1.53millionhaand3.01millionha(dashedlineinfigure5-28).intensityharvestingcanhaveasubstantialeffectonarea-basedTheRPASouthRegionhadthehighestremovalrateinallyears,metrics,eveniftotalvolumeremovedonlychangesslightly.accountingformorethan65percentofallremovalseachyear,Forexample,thePacificNorthwest’shighlyproductiveforestsandthemostvariabilityfromyeartoyear.AlthoughsubstantiallyreportanaverageextractionintensityroughlytwiceashighlowerthantheSouthRegion,theNorthRegionhadthenexthighestannualremovalrateonaverage,followedbythePacificCoastandRockyMountainRegions.2020ResourcesPlanningActAssessment5-33asintheSoutheast’sforests(200m3/haversus100m3/ha)MultipleForestDisturbances:A(Maseketal.2011).Forevery1m3decreaseintotalannualNeighborhoodPerspectivevolumeharvestedintheSouth,thereisa0.5hadecreaseinharvestedarea,whereasthesamedecreaseinvolume❖Ninety-fourpercentofplaceswhereforestwasharvested(1m3)leadstoa1hadecreaseinharvestareainthePacificNorthwest.Whilevolumemetricsremainsteadyorlostbetween2001and2010hadatleastoneshowonlyslighttrends,area-basedsummariesofremovalsidentifiabledisturbanceprocessoccurringmaybemorevariablethroughtime.Thedisconnectbetweennearby,and15percentofforestlosslocationsvolumeandarea-basedmetricsmaybegreaterespeciallyinexperiencedcumulativepressuresfrommorelocationswithlowerproductivityand/ormorevariableharvestthanonechangeprocess.intensities,suchastheSouth(figure5-28).❖Duringthesametime,nearlyhalfofallforestareaFigure5-28.Annualareasofforestcanopylosseventsattributedtoremovalsandpercentoftotalforestthatwaslosttotheseremovalevents,1986to2010,wasexposedtoforestremovalsoccurringnearby,byRPAregion.Regionalareasarestackedontopofoneanother,sothatthewithsmallerproportionsexposedtostressordottedlinerepresentsthetotalareafortheconterminousUnitedStates.Seefire,andevensmallerareasexposedtolandtextforadiscussionofremovalareascomparedwithremovalvolumes.conversion.❖MostforesttypegroupsintheEasternUnitedStateshadhigherexposuretoremovalsandlowerexposuretostressandfire.Incontrast,mostforesttypegroupsintheWesternUnitedStateshadhigherratesofexposuretostressandfireandrelativelylowerexposuretoremovals.PacificCoastRockyMountainNorthSouthMultipleDisturbancesNearSource:Schleeweisetal.(2020).RecentForestLossDiscussingremovalsintermsofbothareaandvolumefromEarliersectionsinthischapterfocusedonindividualtraditionalinventoriesandremotesensinggivesamorerobustdisturbancesoccurringinisolation.Manydisturbanceunderstandingofthedisturbance.Informationfromremoteprocessesoccurincloseproximitytooneanother,andsensing,likethatreportedhere,canincludehighertemporalcantogetherputcumulativepressureonforestsanddetailthantreevolumeinformationfromforestinventories,theirresources(Drummondetal.2017,DrummondandwhileforestinventorydatacanincludemoredetailontheLoveland2010).Byassessingtheextenttowhichmultiplesize,age,orspeciesofthetreesremovedandthemanagementdisturbanceshaveoccurredinornearforests,wecangainobjectivesoftheremoval.Recentstudieshaveshownthatininsightintothosecumulativepressures.someareas,suchastheSouthernStates,intensityandratioofpartialtoclear-cutharvestcanvarydramaticallyonanannualRegionaltrendsandratesofforestcoverchangehavetimestep(Huangetal.2015,Taoetal.2019).Inthefuture,variedsince2001acrosstheconterminousUnitedStatescombininginformationfromsatelliteimagetimeserieswith(seetheLandResourcesChapter).From2001to2010,plot-baseddatacanprovideadditionalinformationandallowathetotalgrossforestlosswasapproximately140,000km2widerrangeofremovalintensitiestobedetectedandmapped(14millionha,6percentofthe2001forestarea).Togain(Taoetal.2019).Additionally,outcome-basedmetrics,suchinsightsaboutwhichdisturbanceprocesseshaveoccurredasthoserelatedtotheeffectivenessofremovalsatreducingnearforestloss,wesummarizedtheco-occurrenceoffuelsonforestlandwithhighfireriskbutlowvolumeandmultipledisturbancesnearby.Weevaluateddisturbancesacreage,couldbeagoodadditiontoarea-andvolume-basedoccurringwithina4.41-haneighborhoodofforestcovermetricsinnationalreportingandassessment.lossfrom2001to2010,withforestcoverlossdefinedaspixelsthatchangedfromforesttononforestoverthistimeperiodintheNationalLandCoverDatabase(USGS2019a,2019b).Althoughco-occurrencesofcommonforestdisturbanceprocessesarerarelymappedoverlargespatialextents,therehavebeenrecentstridesincreatingthedatasetsneededforsuchanalysesintheUnitedStates(Huoetal.2019;Schleeweisetal.2013,2020;Vogelmannetal.2011).Thesenewdisturbanceattributiondataallownovelinsightsaboutthelikelycausesofchange(Riittersetal.2020).ThedatadescribedinthesectionForestRemovalAreasuseaconsistentmethodologytomapforest5-34FutureofAmerica’sForestsandRangelandsEffectsofAirPollutiononForestEcosystemsImpairedairqualitystressesforestandrangelandCriticalloadsaredepositionlevelsabovewhichecosystems,leadingtoalteredspeciescomposition,componentsofforestsorrangelandecosystemsexperiencemodifiedecologicalfunction,andimpactstoecosystemharmfulecologicaleffects;depositionlevelsgreaterthangoodsandservices(forexample,Agathokleousetal.2020,thecriticalloadresultinacriticalloadexceedanceforPardoetal.2011,Sams2007).Airqualitytrendsintheagivenecosystemcomponent(Porteretal.2005).WeUnitedStatesarethereforerelevantandimportanttothecanidentifywhereecosystemsarelikelyimpactedbyairmanagementofforestsandrangelands.SomeairqualitypollutionbycomparingmapsofpastorfuturedepositioneffectsarealreadyincorporatedintotheRPAwaterqualitywithmapsofcriticalloadthresholds.assessment(seetheWaterResourcesChapter)andforestproductivitymodeling(seetheForestResourcesChapter).HistoricalandrecenttrendsinexceedancesofsurfaceHereweprovideanoverviewofspecifictypesofairwatercriticalloadscanserveasacasestudytohighlightpollutants,recentandfuturetrendsinthedepositionoftheeffectofairpollutiononrenewableresources.Surfaceairpollution,andpotentialeffectsonforestandrangelandwatersintheUnitedStates,especiallyintheNortheastandecosystemsandresources.alongtheAppalachianMountains,havebeenimpactedbydepositionofsulfurandnitrogenintheformof“acidEmissionsfromavarietyofsources,includingagriculture,rain,”predominantlyfromindustrialandfossilfueloilandgasdevelopment,fossilfuelcombustion,andsources(Aberetal.1989,Driscolletal.2001,Greaveretnaturalsourcessuchaswildfire,contributetoimpairedairal.2012).Asemissionsandacidrainincreasedthroughoutquality(USEPA2020).Depositionofemittedpollutantsthe20thcentury(Gallowayetal.2004)(figures5-29,fromtheairtothegroundleadstoeffectsonforestand5-30a,5-30b),surfacewatercriticalloadswereexceededrangelandecosystemsthatvarybypollutant(DavidsonatmanylocationsintheRPANorthandSouthRegionsetal.2012,Fennetal.2011).Forexample,sulfurand(figure5-30b).Resultingacidificationdegradedsoils,nitrogendepositionhavebeenshowntosignificantlywhichaffectedwaterchemistryandreducedthepresenceimpactforestresourcesthroughtheacidificationofsoilsofaquaticorganisms,frommacroinvertebratestogameandsurfacewaters,leadingtodecreasedgrowthofcertainspeciesoffish.Theseeffectsonhabitatsandwildlifetreespecies,reducedspeciesrichness,anddiminishedultimatelyimpactedecosystemservicessuchasdrinkingnutrientavailability(Fennetal.2011,Pardoetal.2011).waterandrecreation(Beieretal.2017)Figure5-29.Historical(1850to2000)andprojected(2000to2070)averageannualaciddepositionforeachRPAregion.ProjectionsareshownforRCPs4.5and8.5.Aciddepositionisthetotaldepositionofsulfurandnitrogencompounds.Dashedlinesrepresenttimepointswheredepositionvaluesareusedtomapcriticalloadexceedancesinfigure5-30.TotalAcidDeposition(Nitrogen+Sulfur)HistoricalProjected-RCP4.5Projected-RCP8.5N+SDeposition(eq/ha-yr)RPARegionN+SDeposition(eq/ha-yr)N+SDeposition(eq/ha-yr)NorthSouthRockyMtnPacificCoastYearYearYearha=hectares;N=nitrogen;RCP=RepresentativeConcentrationPathway;S=sulfur.Sources:Lamarqueetal.2010(historical)andLamarqueetal.2011(projection),accessedthroughtheEnvironmentalProtectionAgency’sCriticalLoadsMapperwebtool(https://clmapper.epa.gov/).2020ResourcesPlanningActAssessment5-35Figure5-30.Mapsofcriticalloadexceedancesforsurfacewateracidificationforfourperiodsfrom1850to2070:(a)1850,beforeintenseindustrializationandaccompanyingincreasesinemissionsandaciddeposition;(b)1980atpeakofemissionsandaciddepositioninmostareasoftheU.S.;(c)2020;and(d)2070.Negativecriticalloadexceedancevalues(shadesofblue)indicatethataciddepositionlevelsarebelowthecriticalload,whilepositivecriticalloadexceedancevalues(shadesofred)meanthataciddepositionisabovethecriticalloadandindicatethatthatareaislikelyexperiencingecologicalimpacts.For2020and2070,mapsaredepictingdepositionlevelsfromprojectionsbasedonRCP8.5.(a)(b)(c)(d)N=nitrogen;RCP=RepresentativeConcentrationPathway;S=sulfur.TotalN+S(eq)Sources:Lamarqueetal.2010(historical)andLamarqueetal.2011(projection),accessed<-1,000-350to-700to70350to1,000throughtheEnvironmentalProtectionAgency’sCriticalLoadsMapperwebtool(https://-1,000to-350-70to070to350>1,000clmapper.epa.gov/).CongresspassedtheCleanAirActAmendmentsof1990Sutherlandetal.2015)(figure5-30c).Insomelocations,toreducetheimpactsofacidrainbytargetingsulfurhowever,theseverityofaciddepositionand/ortheand,toalesserdegree,nitrogenemissions(Greaveretal.sensitivityoftheecosystemcreatedlong-lastingeffectsthat2012).Subsequentemissionsreductionshavedecreasedcouldcontinuetoimpactecosystemsintothefuture(Burnsaciddepositionsubstantiallyinallregions,fromanearlyetal.2020,Sullivanetal.2018).25-percentreductionintheRockyMountainRegiontoanover50-percentreductionintheNorthRegion(figureFutureprojectionsofaciddepositionanditsimpactshave5-29).Innumerousplaces,thesereductionshaveeliminatedbeenmadeforbothselectedRPAclimatefutures:RCPscriticalloadexceedancesandallowedecosystemsto4.5and8.5(Clarketal.2018a,Lamarqueetal.2010,recover,sometothepointofallowingthereintroductionof2011).Aciddepositionisprojectedtocontinuetodecreasepreviouslyextirpatedfishspecies(Sullivanetal.2018,underRCP4.5and,toalesserextent,RCP8.5,exceptfor5-36FutureofAmerica’sForestsandRangelandstheRockyMountainRegionunderRCP8.5(figure5-29).etal.2001,Davidsonetal.2012,Sullivanetal.2018).ProjectedincreasesintheRockyMountainRegionareProjecteddecreasesinaciddepositionareexpectedtoprimarilydrivenbynitrogendeposition,whichismorecontinuetodecreasecriticalloadexceedancesandfurthercomplicatedthansulfurdepositionwithabroadersuitereduceimpactstosurfacewaters(figure5-30d);however,ofchemicalcompounds,sources,andeffects(Gallowaythechangingchemicalcompositionofdepositionmeansetal.2004,GruberandGalloway2008).AlthoughthesomeecosystemsmayexperienceadditionalimpactsandaCleanAirActAmendmentsof1990decreasedemissionsdisruptedrecovery.Researchonairpollutionimpactsandofnitrogencompoundsthatcontributetoacidification,thedevelopmentofcriticalloadshaveenabledmappingemissionsofothernitrogencompoundshavecontinuedimpactstoecosystemgoodsandservicesanddevelopingtoincrease,complicatingecosystemrecovery(Butlerprojectionsoffutureimpacts.canopycoverlossattributednotonlytoremoval,butalsosummarizedisturbanceoccurrenceonlyforareaswheretofireand“stress”(drought,insects,diseases)(Schleeweisforestlosswasobserved,notforallforestland.etal.2020).Ouranalysisalsoincludedtwotypesofdisturbancefromland-usechange:increasedagricultureNinety-fourpercentofpixelswhereforestcoverwaslostanddevelopmentfromtheNationalLandCoverDatabasehadatleastonedisturbanceidentifiednearby,whiletwoor(Homeretal.2020;USGS2019a,2019b).Ourestimatesofmoredisturbanceprocesseswereidentifiednear15percenttheareawithcombinedpressuresina4.41-haneighborhoodofallforestlosslocations.Removalwasthemostcommonaredifferentfromthedisturbanceareasreportedelsewheredisturbanceprocess,occurringnearatotalof109,187km2inthisdocument.Here,weconsideradisturbanceprocess(10.9millionha)offorestcoverloss(blackhorizontalbartohaveaffectedaparticularforestedlocationifthatprocessinfigure5-31).Firewasnextmostcommon,occurringwasobservedatthatlocationoronforestnearby.Wenear29,060km2(2.9millionha)offorestcoverloss.Figure5-31.Summaryofforestdisturbanceprocessesforlocationswithforestcoverloss,2001to2010.Thefiguredepictstheoccurrenceofeachprocessaloneorincombinationwithoneormoreothers.Thehorizontalblackbarsindicatethetotalareaofforestcoverlossthathadeachprocessinitslocalneighborhood,whetheraloneorincombinationwithanotherprocess.Theverticalbarsindicatetheareaofforestcoverlossthathadauniquecombinationofprocesses.Thecombinationscapturedineachverticalbararedepictedbyblackdotsbeneaththeverticalbar,withaconnectinglineiftwoormoreareincludedintheset.PacificCoastRockyMountainNorthSouth2020ResourcesPlanningActAssessment5-37Stress,conversiontodevelopedlanduse,andconversiontoFigure5-33.ProportionofFIAforestlandineachFIAforesttypegroupinagriculturallandusewerelesscommon(<10,000km2or<1theEasternUnitedStatesthatwasexposedtoremoval,stress,andfireevents,millionhaeach).2001to2010.ExposureisdefinedasanobservedlossofforestcanopywithinRemovaloccurredalonein83percent(90,781km2or9.1a4.41-haneighborhoodsurroundingFIAplotlocations.Foresttypegroupsmillionha)oftheplaceswhereitoccurred(figure5-31).arearrangedbydecreasingareafromtoplefttobottomright(seefigure5-8Sixty-sixpercent(72,417km2or7.2millionha)oftheforareas).Someoftheaspen/birchgroupoccursintheWesternUnitedStates.removalthatoccurrednearforestcoverlossoccurredintheRPASouthRegion.Whereremovalco-occurredwithFIA=ForestInventoryandAnalysis;ha=hectares.otherprocesses,itwasfoundmostoftenwitheitherfireorSource:Schleeweisetal.2020.increasesindevelopedlanduse.Afterremovalalone,thenextmostcommonprocessnearusesco-occurredmostfrequentlywithremoval.Whilethisforestcoverlosswasfirealone,whichoccurredtwiceasanalysissummarizeseventsoccurringnearbyoneanotheroftenaloneaswithotherprocesses(19,431km2or1.9duringa10-yearperiodandnotinsequencewithonemillionhaversus9,629km2or1.0millionha).Sixty-twoanotheratthesameforestedlocation,theco-occurrenceofpercent(11,988km2or1.2millionha)oftheplaceswherethetwosuggeststhatthoseremovaleventsmayberelatedfireeventsoccurredalonenearforestcoverlosswereinthetolanduseconversion.AnincreaseindevelopedlanduseRPARockyMountainRegion,withanadditionalone-third(aloneorcombined)was2.5timesmorecommonthan(6,510km2or651,000ha)occurringinthePacificCoastincreasedagriculture(aloneorcombined)nearplaceswhereRegion.Whenfirewasobservedwithanotherprocess,itforestwaslost,suggestingthatforestcoverwasmoreoftenwasfoundmostoftenwithremoval.lostfordevelopmentthanforagriculture.StresswasobservednearforestcoverlossmuchlessThedifferencesinthefrequenciesoftheseprocessesbyfrequentlythanremovalorfire,andco-occurredwithregionhaveimportantimplicationsforforestlossandremoval,fire,orbothprocesses11timesmoreoftenthanchange.IntheRPASouthRegion,removalalonewasbyfaritoccurredalone.Theco-occurrenceofstresswithfirethemostcommonprocessobservednearforestcoverloss,andremovalsreinforcesotherresearchthathasfounddemonstratingforestmanagement.Whileco-occurrenceofcoincidencebetweeninsectoutbreaks,drought,fire,andremovalandincreaseddevelopmentwasrarenationally,removal(Hoodetal.2017,Rhoadesetal.2018).itoccurredmostoftenintheSouthRegion,reflectingtheLikestress,increasesindevelopedandagriculturallandfactthathousingdevelopmentisacomparativelyfrequentusesalsooccurrednearotherprocessesmorefrequentlyphenomenonintheregion’sforests(Radeloffetal.2018).thanbythemselves.ConversiontowardbothoftheselandSimilarly,removalaloneandtheco-occurrenceofremovalwithincreaseddevelopmentwerethetoptwotypesofFigure5-32.ProportionofFIAforestlandexposedtoremoval,stress,fire,processesoccurringnearforestlossintheNorthRegion.increaseindevelopedland,orincreaseinagricultureobservedwithina4.41-TheseresultssuggestthatforestsintheNorthandSouthhaneighborhoodfrom2001to2010.Regionsfacesimilarpressures.However,theareasofforestFIA=ForestInventoryandAnalysis.Sources:Removals,fire,andstresscamefromcanopydisturbanceattributiondatafor2001to2010andrepresenttheproportionexposedtoatleastoneeventoverthatperiod(Schleeweisetal.2020),whileincreaseinagricultureand/ordevelopedlandusescamefromNLCDdatafor2001to2011andrepresenttheproportionexposedtoatleastoneeventoverthatperiod(Homeretal.2020;U.S.GeologicalSurvey2019a,2019b).5-38FutureofAmerica’sForestsandRangelandsFigure5-34.ProportionofFIAforestlandineachFIAforesttypegroupineachofthefiveforestcanopycoverdisturbanceprocessestheWesternUnitedStatesthatwasexposedtoremoval,stress,andfireevents,occurringwithina4.41-haneighborhoodfrom2001to2001to2010.Exposureisdefinedasanobservedlossofforestcanopywithin2010.Thissummary,reportedbyforesttypegroup,isa4.41-haneighborhoodsurroundingFIAplotlocations.Foresttypegroupssupplementedbyaparallelanalysisof“core”forestcoverarearrangedbydecreasingareafromtoplefttobottomright(seefigure5-8lossintheLandResourcesChapter.Exposureofforestlandforareas).toremovalduringtheperiod2001to2010wassubstantiallyhigherthananyotherprocess:nearlyhalf(49percent)ofFIA=ForestInventoryandAnalysis;ha=hectares.forestlandwasexposedtoatleastoneremovaleventfrom2001to2010(figure5-32).Bycontrast,only6.2percentandcoverlossassociatedwiththeseeventsweresmallerinthe5.2percentofforestland,respectively,wasexposedtostressNorththanintheSouthRegion(figure5-31),suggestingandfire.EvensmallerportionsofforestlandwereexposedtothatforestsintheSouthfacethesepressuresmoreoften.Inincreasesindevelopedandagriculturallanduses(0.7percentthePacificCoastRegion,removalalonewasthetopprocessand0.4percentofforestland,respectively)(figure5-32).Thisoccurringnearforestloss,butfirealonewasaclosesecond,resulthighlightsthecommonoccurrenceofremovaleventsfollowedbyfireandremovaltogether.TheRockyMountaininforestlandacrossthecountry(Cohenetal.2016),whetherRegionwastheonlyregionwherethemostcommonprocessforsilviculturalorotherpurposes,andconfirmsthehighlywasfirealone,ratherthanremovalalone.ThisregionhasdynamicnatureofforestcoverdocumentedinearlierRPAlessmerchantabletimberlandthanotherregions(Oswaltreports(Nelsonetal.2020).Whilelocallyimportant,increasesetal.2019),ahigherproportionofforestthatispublicorinagricultureanddevelopedlandarerelativelyrarenearFIAprotected(Nelsonetal.2020),andmoreareaburnedduringforestlandoverall(figure5-32),andthereforeexcludedfromtheperiodofobservation(seethesectionFireinForestsandfurtheranalyses.Rangelands).TheRockyMountainRegionalsocontainedthemostobservationsofstress,aloneandincombinationTheforestcanopydisturbancesdescribedaboveoccurinwithotherprocesses,whichreflectsthehighratesofinsectsomeforesttypesmoreoftenthanothers.Liketheresultsanddiseaseactivityaswellasdroughtinthatregion.forallforestland,manyindividualFIAforesttypegroups(figure5-8)hadahigherexposuretoremovaleventsthantoExposureofAllForestLandstoanyotherprocess(figures5-33,5-34).Specifically,theforestDisturbanceProcessestypegroupsthatarerelativelywidespreadintheEasternUnitedStateswereamongthosewithahighproportionTogaininsightsaboutthedegreetowhichallcurrentforestexposedtoremovalandlittleornoexposuretofireandstresslandintheconterminousUnitedStateswasexposedtoevents(figure5-33).Examplesincludetheoak/hickory,disturbancesoccurringnearby,weappliedasimilarapproachloblolly/shortleafpine,andmaple/beech/birchgroups,astoexistingFIAforestland(asopposedtoforestlossareas).wellasthewhite/red/jackpinegroup,whichhasasmallerWesummarizedtheproportionofFIAforestlandareawithrange(figures5-8,5-33).ThisresultfurtherunderscorestherelativelylargearealfootprintofremovalintheEasternUnitedStates.Eighty-ninepercentofthecommerciallyimportantloblolly/shortleafgroupwasexposedtoremovalnearbyoverthe10-yearperiod.Relativelyhighexposuretoremovalisnotunexpectedinthisgroup,andremovalfortimberharvestisusuallyquicklyfollowedbyreplantingandintensivemanagement(Drummondetal.2017).Whilefiremayoccurrelativelyfrequentlyinsomeofthoseeasternforesttypes,itgenerallyisoflowenoughseveritynottodisturbtheforestcanopyandthereforelargelydoesnotappearintheeasterntypegroups.Thelongleaf/slashpinegroupisanotableexception,having12percentoftotalareaexposedtofireoverthe10-yearperiod,likelybecausefrequentfireisimportantformaintainingecosystemfunctionandbiodiversity(Peetetal.2018).Theaspen/birchtypegroupwastheonlyeasterngroupwithnotableexposuretostress(14percent),butsomeofthattypegroupalsooccursintheWesternUnitedStates.ForesttypegroupsoccurringprimarilyintheWesternUnitedStatestendedtohavegreaterexposuretofireandstress2020ResourcesPlanningActAssessment5-39eventsthanthoseoccurringprimarilyintheEasternUnitedManagementImplicationsStates(figure5-34).Thisresultisconsistentwiththehighratesoflarge,high-severitywildfires,drought,andinsectDisturbanceisrelevanttobothmanagementandpolicy,disturbancesshownforthewesternregionsintheearlierespeciallyasclimatechanges,humanpopulationsincrease,sectionsofthischapter.TheDouglas-fir,ponderosapine,andanddevelopedlanduseexpands.Managementactions,Californiamixedconifertypegroupshadhigherexposuretopolicies,andinitiativescanhelprestorenaturaldisturbancestressandfirethananyoftheeasterntypegroups,whilestillregimes,whereappropriate,andincreasethecapacityofhavingrelativelyhighexposuretoremoval,underscoringforestsandrangelandstoadapttochangingregimesorthemultiplepressuresthoseforestsface.Thefir/spruce/recoverfollowingdisturbance.Inthoseways,managementmountainhemlockandlodgepolepinetypegroupswerealsocanreducethevulnerabilityofforestsandrangelandstoexposedtoallthreeforestcanopythreats,withexposuredisturbancesthemselvesandhelpincreasetheresilienceoftostressbeinghighestforbothgroupsduringthe10-yearthoseecosystemstoclimatechangeandotherglobalchangeperiod.Thehemlock/Sitkaspruceandalder/maplegroupsdrivers.Asinthecaseofremovals,however,managementhadrelativelylowexposuretobothstressandfire,asactionscanthemselvesbeconsidereddisturbances.Whileexpectedgiventhedistributionsofthoseforesttypegroupssomemanagementimplicationsofsingledisturbancetypesinrelativelymoistsites.Thepinyon/juniperandwoodlandinforestsorrangelandshavebeenmentionedthroughoutthishardwoodstypegroupshadlowexposuretoallthreecanopychapter,afewcross-cuttingideasapply.disturbancetypes;however,weknowthattheseforestsaresubjecttodisturbanceeventsincludingdrought,asshowninInsomeplaces,managementofforestsandrangelandsthesectionDroughtinForestsandRangelands.Giventhattomitigatemultipledisturbancesmaybedesirable.OurtheforestcanopyisoftenrelativelysparseintheseforestanalysisshowsthatforestsintheRPAPacificCoastRegiontypes,disturbanceeventsmaynotalwaysleadtomeasurablemaybeparticularlyexposedtomultipleco-occurringlossoftheforestcanopy,meaningthatthosedisturbancedisturbances.DryforestsofCaliforniahaveexperiencedeventsarelikelynotwellcapturedinthisexposureanalysisrecenttreemortalityduetointeractionsofdrought,wildfires,fortheseforesttypegroups.andbarkbeetles(Fettigetal.2019).ForestthinningandprescribedfiretogetherhavereducedtheeffectsofthoseWhilethisanalysisfocusedonexposureofforestsandinteractingdisturbances(Knappetal.2021).Similarly,fuelforesttypegroupstodisturbance,theresultscanbeusedtreatmentslikethinninginforestsofthePacificNorthwestinconjunctionwithinformationonthesensitivitiesofmayhelpincreaseresiliencetofire,insects,anddrought,andtheseforeststothedisturbanceprocessestodeterminefacilitatepost-disturbancerecovery(Halofskyetal.2020).theecologicaloreconomicimpactsofthesedisturbances.OneexampleofdemonstratedhighsensitivitytomultipleAsthecharacteristicsofdisturbancesanddisturbancedisturbanceprocessesoccursindryportionsofDouglas-firregimeschange—becomingmoresevere,morefrequent,andponderosapineforestsoftheWesternUnitedStates,longerinduration,orspreadingtopreviouslyunaffectedwherehigh-severitywildfirescombinedwithwarmanddryecosystems—theycouldchallengetheeffectivenessofclimatecancausetreeregenerationfailureandsubsequentexistingmanagementtechniquesandparadigms,andmayconversiontononforest(Coopetal.2020,Davisetal.forcechangesoradjustments.Forexample,management2019,2020).Foresttypegroupsrepresentassemblagesofactionsthatincludeacceptingarangeoffireseveritieswhentreespecies,eachwithitsowndisturbancesensitivitiestoandwheretheyaresafe,reducingwildfireoccurrenceintheconsider.Asaresult,shiftsinforestspeciescompositionwildlandurbaninterface(WUI),andimprovedplanningofmaybelikelybecauseofdifferentialresponsesoftreeresidentialcommunitiestoavoidorwithstandwildfiresmayspeciestothesedisturbanceprocesses.SummariesofthesebeappropriateintheWesternUnitedStates,whereclimatedisturbanceprocessesatafinerlevelofforestclassification,andland-usechangeareincreasingboththetotalareaburnedsuchasbyspecies,orwithinmorerestrictedareas,wouldbywildfiresandtheareaburnedintheWUI(Calkinetal.likelyallowformoreinsightabouthowthesedisturbances2014,Kellyetal.2020,Radeloffetal.2018,Schoennagelaffectforests.Inaddition,summariesofexposureofFIAetal.2017).Inrangelands,managersaresearchingforforestlandtoadditionaldisturbancesnotincludedhere,suchnovelapproachestocurbthespreadofnonnativeannualashurricanesandotherstormsandsealevelrise(seetheplants,especiallycheatgrass(Bromustectorum)andredsidebarSeaLevelRiseEffectsonForestsforasynthesisofbrome(Bromusrubens),tobreaktheannualgrass-firecycle.forestimpacts)wouldprovideamoreholisticpictureoftheIncorporatingmoreflexiblegrazingstrategies,specificallydisturbancesandstressorsfacingourforests.targetedgrazingthataimstoreducethecoverofthesespecies,showspromise,andtheUSDAForestServiceandU.S.BureauofLandManagementareincreasinglylookingforwayspromoteandexpandtargetedgrazing.Doingsofacesseveralchallenges,includingincreasedflexibilityin5-40FutureofAmerica’sForestsandRangelandsgrazingallotmentadministration.NewtechnologiessuchasofdroughtcombinewithinvasivespeciestoexacerbatetheRangelandProductionMonitoringSystem(Reevesetal.changesinfireregimesinmanyplaces.Partnerships,2020,2021)arepartofastrategicsupportsystemthatmayespeciallywhenconductedatlargescalesorwhenreplicatedhelpmanagersdetectnonnativegrassesandidentifytargetedindifferentregions,couldbenefitfuturemanagementofagrazingopportunities.widevarietyofdisturbancesinforestsandrangelands.Inadditiontochangingdisturbanceregimes,theabilityforConclusionsprofessionalstoconductmanagementtomitigatelargerormoreseveredisturbancesandincreaseecosystemresilienceDisturbanceisaconstantpresenceinmanyforestandmayalsobeaffectedbyglobalchangedrivers.Asthearearangelandecosystems.ForthefirsttimeinanRPAandseverityofwildfiresincreasesandtheWUIexpandsinAssessment,theanalysisinthischapterprovidesatheWesternUnitedStates,wildfiremanagementisbecomingcomprehensivelookattherecent,andinafewcases,futuremorechallenging.PrescribedburningisalreadybecomingdisturbancesinbothforestsandrangelandsacrosstheUnitedmoredifficultinsomeplaces,atleastinpartduetoclimateStates.Ourresultshighlightthatmanyofthesedisturbancesandlandusechange,andincreasedchallengesareprojectedarebecomingmorefrequent,widespread,orsevereovertime,inthefuture.Reductionsinthenumberofdayswithandthatregionalvariabilityexistsinthetype,amount,andsuitablemeteorologicalconditionsforprescribedburningintensityofdisturbancesthatoccurinforestsandrangelands.areprojectedinthefutureintheSouthRegion(Kupferetal.2020),suggestingthatdecreasesintheareaburnedareIntermsofrecenthistoricaltrends,theaverageannualarealikely,especiallyastheexpandingWUIplacesadditionalburnedbyfireinbothforestsandrangelandshasincreasedchallengesonburning(seethesidebarCOVID-19asanationwideandinallRPAregionsexcepttheNorthRegion.ConstraintonPrescribedBurningintheSoutheasternUnitedDroughtexposurehasbeenhighinforestsandrangelandsinStatesformoreinformationonrecentchallenges).SuchtheWest,particularlythePacificCoastRegion.Nonnativereductionsinwildfiremanagement,prescribedburning,orinvasiveplantshavebeenmostprevalentinforestsnearanyothermanagement,canresultinforestsandrangelandsagriculturalanddevelopedareasintheEast,andinrangelandsthatarelessresilientthroughtime,havingconcomitantwithincountiesinCalifornia.Inadditiontothedirecteffectsontheresultingresourcesandservices.exposureofforeststodisturbances,manyforestsexistindynamiclandscapesthatexperiencemultipledisturbancePartnershipsandcollaborationsamongscientists,managers,pressures,includingcombinationsofremovals,stress,andandpublicandprivatelandownerscanhelpaddressthefire,aswellasconversionoflandusetoagricultureorincreasingneedformanagement,growingchallengesdevelopment.associatedwithmanagement,anduncertaintiesinfutureconditions(Glicketal.2021).AdaptivesilvicultureforLookingaheadto2070,thedisturbancetypesdiscussedinclimatechangeisaneffortamongscientistsandmanagerstothischapterhavethepotentialtobecomemorefrequent,identifythemanagementactionsthatarelikelytoincreasethewidespread,orsevereinmanylocations(withthenotableadaptivecapacityofforeststotheeffectsofchangingclimate,exceptionofaciddepositioninforests,seethesidebarincludingdisturbance(Nageletal.2017).SeveralrecentEffectsofAirQualityonForestEcosystems).ForestinitiativesinvolvingtheUSDAForestServicehaveaimedmortalityfromfireisexpectednationwideandwithineachtocreatepartnershipsamongagenciestoidentifytreatmentsRPAregion.Increasesintheareaofmoderate-andhigh-andothermanagementactionstomeetmultipleobjectives,severityfirearealsoprojectedinmanylocations,especiallyincludingreducingriskofwildfireandotherdisturbancesintheRPAPacificCoastandSouthRegions.Forestand(USDAForestService2018).TheseinitiativesincluderangelandexposuretodroughtisprojectedtoincreaseastheCollaborativeForestLandscapeRestorationProgram,well,particularlyforecosystemsintheSouthwest.WhiletheWildfireCrisisStrategy,andtheSharedStewardshipnotexplicitlyprojected,literaturesummarizedinthisStrategy.Inrangelands,theecologicalandeconomicthreatchaptersuggestspotentialforincreasingthreatsfrominsectsthatinvasivegrassesposetolocalcommunitieshasinspiredanddiseaseandnonnativeinvasiveplants.anunprecedentedlevelofcooperationamonglandmanagers,nonprofits,governmentagencies,andthebusinesscommunity.TheNation’sforestsandrangelandsfacepressuresfromOneexampleofacooperativemodelistheSouthernArizonathesedisturbancesagainstabackdropofchangingclimate,BuffelgrassCoordinationCenter,whichusescross-jurisdictionsocioeconomicconditions,andlanduse.Thesedisturbances,coordinationandcommunityengagementtohelpcontrolaloneandinconcert,areaffectingforestsandrangelandsbuffelgrass(Pennisetumciliare),aninvasiveperennialandthegoodsandservicestheyprovide.Forexample,threateningseveralrangelandecosystems.FosteringmorefireanddroughttogetherarealreadytransformingsomecooperationandcoordinationthroughoutU.S.rangelandsmaydryforeststograsslandsintheWesternUnitedStates,andbebeneficialinthefuture,asincreasedfrequencyanddurationtheco-occurrenceofdroughtwithextremeheatprecededforestmortalityandreducedrangelandproductionin2020ResourcesPlanningActAssessment5-41Texas.Themagnitudeofdisturbanceimpactonecosystems,Disturbancesareintegralpartsofforestandrangelandhowever,canvarywithanumberoffactors,includingecosystemsthataffectthegoodsandservicesthosespeciescompositionandlandscapecharacteristics.Notallecosystemsprovide.Disturbancesarelikelytocontinuefiresarethreatstoforestsorrangelands,andnotallforeststoincreaseinmanylocations,especiallyasclimateorrangelandshavethesamevulnerabilitytodrought.changes,humanpopulationincreases,anddevelopedTheseadditionalfactorsarerelevanttocomprehensivelanduseexpands.Informationaboutstatusandtrendsinassessmentofeffectsonforestsandrangelands.Theimpactsthesedisturbancesovertimeinformsforestandrangelandfromdisturbancecanalsobeaffectedbymanagement,asmanagementthatcanbetterfacilitateadaptationoftheincreasingevidenceispointingtotheimportanceofactionsNation’sforestsandrangelandstoglobalchange.likeprescribedfireandthinningforimprovingtheresilienceofforeststodisturbanceandotherglobalchangedrivers.SeaLevelRiseEffectsonForestsPastandFutureSeaLevelRisefuturespaceforcoastalforestretreatisacriticalfactordeterminingfuturegainorlossofsuchecosystemsandThermalexpansionofoceanwatersandglacialandiceisaffectedbymanyfactors,suchastheeconomicfactorssheetmelting,bothconsequencesofglobalwarming,havedrivingcoastallandusechanges(KirwanandGedan2019,contributedtosealevelrise(SLR)overthepast200years.Schuerchetal.2018).StudiesindicatethatthepaceofglobalmeanSLRhasacceleratedintherecentpast,fromabout0.05inchesperTwotypesofcoastalforestscanbedistinguishedforyearduring1901to1990to0.12to0.14inchesperyearthepurposeofdescribingSLReffects:estuarinecoastalduringtheperiod1993to2010(Dangendorfetal.2017,foreststhatareadaptedtosaltwater(e.g.,mangrove,Hayetal.2015).WhiletherateoffutureSLRdependsbeach,andpeatswampforests),andfreshwatercoastalonglobaltemperaturechange,currentprojectionsareforeststhatcannottoleratesalt.Theeffectsonandforglobalmeansealeveltoriseby0.4to2.5mby2100likelihoodoflosingcoastalforestdiffersbetweenthese(Oppenheimeretal.2019).twotypesofforest.Coastalforestretreats,replacementofcoastalforestsTheeffectsofSLRoncoastalforeststhatareadaptedtobysaltmarsh,andtheappearanceofghostforests(deadsaltwaterareprojectedtobeminimalatthecurrentandtreesadjacenttomarshes)duetoSLRhavealreadyprojectedmid-centurySLR,althoughseveralstudiesbeenobservedonlow-lyingcoastalandestuarinesuggestthatmangroveforestsarethreatenedinmanylandscapes(KirwanandGedan2019).FutureSLRcouldpartsoftheworldandarenotkeepingpacewithlocalleadtopermanentinundation,increasedfrequencyandSLRrates(Friessetal.2019).Forexample,inthetropicsintensityoffloodingfromstormsurges,increasedcoastalunderthehigh-warmingscenario(RCP8.5),relativeSLRerosion,andexpandedsaltwaterintrusionintothesoil,isexpectedtoexceedthetoleranceofmangrovesbecausegroundwater,andfreshwatersystems.This,inturn,ratesofSLRinthetropicsareexpectedtobehigherthanwillresultinloss,alteration,anddegradationofcoastaltheglobalaverage(Saintilanetal.2020).Thelikelihoodecosystemsandnaturalresources,includingforestsandoflosingcoastalforeststoSLRdependsonmanyfactors,wetlands(KirwanandGedan2019,Schuerchetal.2018),suchasthelocalratesofSLRandtherateofsedimentwhichcanhaveindirecteffectsontheforestsector,accretionfortheseecosystems.includingalteredsupplyanddemandconditionsinmarketsforecosystemservicesandforestgoods.LimitedresearchisavailableontheeffectsofSLRonfreshwatercoastalforests,andmostofourunderstandingDirectEffectsofSLRonCoastalForestsisbasedonresearchconductedintheUnitedStates.IncreasingsalineandfrequentfloodingarethoughttoDirecteffectsofSLRonforestsinclude:(1)lossofcoastalcausedeclinesinforesthealthandproductivity,basalforestsduetofloodingandextremesealeveleventssuchareaandtreedensity,speciesdiversity,seedgerminationasstormsurgesandtidalwaves,and(2)alteredstructure,andregeneration,andincreasedtreemortality(Griegercomposition,growth,regeneration,andproductivityetal.2020).Ghostforestsarealsoreportedprimarilyofcoastalforestsduetosaltwaterintrusion,impededalongtheAtlanticcoastofNorthAmerica,whereSLRdrainage,andflooding.Theavailabilityofcurrentandiscurrentlyoccurringatarategreaterthantheglobal5-42FutureofAmerica’sForestsandRangelandsaverage(KirwanandGedan2019,Smartetal.2020).materialsworldwidecouldreduceglobalCO2equivalentThelikelihoodoflosingthesecoastalforeststoSLRwillemissionsby0.47to2.13tonspertonofCO2equivalentdependonlocalratesofSLR,rateofsaltwaterintrusioncarboncontainedinthoseadditionalwoodconstructionintothegroundwater,speciescomposition,andtolerancematerials.Thisemissionsreductionwasconnectedmosttosaltwaterespeciallyforregeneration.directlytothereplacementoffossilfuel-intensivebuildingproductswithwood.IndirectEffectsofSLRontheForestSectorAssessingtheFutureEffectsofSeaLevelRiseonCoastalForests:TheindirecteffectsofSLRontheforestsectorincludeCriticalNeedsdynamicsthataretiedtochangesinsupplyanddemandforforestgoodsandecosystemservices.SLR-inducedCoastalforestsprovideawidevarietyofecosystemlossesinforestareaarelikelytoaffectforestproductservicesglobally,includingprovisioning(fisheries,fuel,marketsbyreducingtheoverallavailabilityoftimber,watersupply,tourism,andculturalresources),regulatingleadingtoacombinationofreducedtimberproductoutput(coastalprotection,carbonsequestration,sustainingandhighertimberprices.Atthesametime,about350tobiodiversity)andsupporting(soil,sedimentandsand480millionpeoplegloballyareprojectedtobeexposedformation,nutrientcycling,habitat).InadditiontoalteringtoSLRby2100(KulpandStrauss2019),requiringexistingcoastalforests,futureSLRcoulddisruptlocalreplacementoftheirpresentdwelling.Asaresult,demandeconomiesandevenresultinhumanitariancrisesaroundforwoodproductsfornewhousingislikelytoincreasetheworld.AdvancingscienceontheeffectsofSLRon(Desmetetal.2018,Haueretal.2020,Nepaletal.2022).coastalforestsiscriticalforassessingtheeffectsanddesigningadaptationstrategies.Increaseddemandsforwoodtorebuildcouldaffectnotonlycoastalregionsbutalsononcoastaltimber-growingImprovedunderstandingandrepresentationofcoastalregionsthroughalteredharvestingactivity,changingprocessesandfeedbacksinglobalforestsectormodelslocalmarketconditions,andalteredinternationalflowsofwouldprovidebetterinformationonsealevelrisefromtradedforestproducts(Nepaletal.2022).Higherproductlocaltoglobalextents,andonitsinteractionswithdemandsbytheconstructionsectorcanleadtoincreasedprojectedlossorgainofcoastalecosystems(Wardetal.forestproductprices,whichcanaffectthecompetitive2020).Onthelocallevel,betterunderstandingofhowadvantageofacountryoraregiontoharvesttimberSLRaffectsgroundwatersalinityandthegraduallossesandtoproduce,consume,andtradeinforestproducts.ofcoastalforestsisneeded.ScientificevidenceonthePriceincreasesalsoprovideaneconomicincentivetolinkagesbetweenSLR-relatedcoastalforesthealthandkeepforestsasforestsortoinvestinintensifiedforestotherforestdisturbances(e.g.,cyclones,insectsandmanagementactivitiessuchasthinningorfertilizationdiseases,invasivespecies,andwildfires)islimitedyet(e.g.,DaigneaultandFavero2021,Nepaletal.2019).criticalforassessingthefullsetofpotentialimpactsofChangesintimberharvests,forestmanagement,andwoodSLR.Establishingtheeffectsofsealevelriseonhabitatproductsmanufacturingactivities,indirectlyinducedforaquaticandterrestrialwildlifeisalsoacriticalneed.bySLRthroughincreasedprices,mayhaveadditionalconsequencesfornetcarbonemissionsmitigationbyCoastalforestconservationeffortscouldbenefitfromtheforestsector.Mitigationpotentialwouldbeaffectedadditionalresearchonthepotentialfeasibilityandthroughchangesinthetotalquantitiesofcarbonstoredoutcomesofalternativecoastalforestconservationinforestsandinharvestedwoodproducts.Likewise,strategies,includingprotectionandexpansionofopenmitigationpotentialwouldalsobeaffectedbyavoidedspacestoenablecoastalecosystemmigration,engineeringfossilcarbonemissionsresultingfromsubstitutionofapproachesthatmightincludethecreationofphysicalwoodformorecarbon-emissions-intensivenonwoodstructures,andassistedmigrationofcoastalecosystemmaterialsinconstruction,suchassteelorconcretespecies.Researchcouldadditionallyexplorehowsuch(Leskinenetal.2018,Nepaletal.2016,Nepaletal.2022,strategiescouldbeimplementedthroughpossibleSathreandO’Connor2010).AsshownbyNepaletal.incentives.Furthermore,becausetheeffectsofSLRare(2022),increasedglobalharveststoaccommodatehighernotrestrictedtocoastalareas,scientificanalysiscouldwoodproductdemandforrebuildingSLR-destroyedfocusonhowthelossesofresidentialandotherstructuresresidentialstructureswouldshrinkglobalforestcarbonbycouldaffectforestlandinlocationsawayfromcoasts.upto2.0percent.However,policiesfavoringrebuildingdestroyedresidentialstructureswithwoodconstruction2020ResourcesPlanningActAssessment5-43ReferencesAndreadis,K.M.;Clark,E.A.;Wood,A.W.;Hamlet,A.F.;Lettenmaier,D.P.2005.Twentieth-centurydroughtintheAbatzoglou,J.T.2013.DevelopmentofgriddedsurfacemeteorologicalconterminousUnitedStates.JournalofHydrometeorology.6(6):dataforecologicalapplicationsandmodelling.InternationalJournalof985–1001.Climatology.33(1):121–131.Archaux,F.;Wolters,V.2006.ImpactofsummerdroughtonforestAbatzoglou,J.T.;Kolden,C.A.2011.ClimatechangeinwesternU.S.biodiversity:whatdoweknow?AnnalsofForestScience.63(6):deserts:potentialforincreasedwildfireandinvasiveannualgrasses.645–652.RangelandEcologyandManagement.64(5):471–478.Ault,T.R.2020.Ontheessentialsofdroughtinachangingclimate.Abatzoglou,J.T.;Kolden,C.A.2013.RelationshipsbetweenScience.368(6488):256–260.climateandmacroscaleareaburnedinthewesternUnitedStates.InternationalJournalofWildlandFire.22(7):1003–1020.Balch,J.K.;Bradley,B.A.;Abatzoglou,J.T.;ChelseaNagy,R.;Fusco,E.J.;Mahood,A.L.2017.Human-startedwildfiresexpandAbatzoglou,J.T.;Kolden,C.A.;Williams,A.P.;Lutz,J.A.;Smith,thefirenicheacrosstheUnitedStates.ProceedingsoftheNationalA.M.S.2017.ClimaticinfluencesoninterannualvariabilityinAcademyofSciencesoftheUnitedStatesofAmerica.114(11):regionalburnseverityacrosswesternU.S.forests.International2946–2951.JournalofWildlandFire.26(4):269–275.Barbero,R.;Abatzoglou,J.T.;Larkin,N.K.;Kolden,C.A.;Stocks,B.Abatzoglou,J.T.;Williams,A.P.2016.Impactofanthropogenic2015.ClimatechangepresentsincreasedpotentialforverylargefiresclimatechangeonwildfireacrosswesternU.S.forests.ProceedingsinthecontiguousUnitedStates.InternationalJournalofWildlandoftheNationalAcademyofSciencesoftheUnitedStatesofFire.24(7):892–899.America.113(42):11770–11775.Barlow,M.;Nigam,S.;Berbery,E.H.2001.ENSO,PacificdecadalAber,J.D.;Nadelhoffer,K.J.;Steudler,P.;Melillo,J.M.1989.variability,andU.S.summertimeprecipitation,drought,andstreamNitrogensaturationinnorthernforestecosystems:excessnitrogenflow.JournalofClimate.14(9):2105–2128.fromfossilfuelcombustionmaystressthebiosphere.BioScience.39(6):378–386.Beguería,S.;Vicente-Serrano,S.M.;Reig,F.;Latorre,B.2014.Standardizedprecipitationevapotranspirationindex(SPEI)revisited:Abt,K.L.;Prestemon,J.P.;Gebert,K.M.2009.WildfiresuppressionParameterfitting,evapotranspirationmodels,tools,datasetsandcostforecastsfortheU.S.ForestService.JournalofForestry.107(4):droughtmonitoring.InternationalJournalofClimatology.34(10):173–178.3001–3023.Agathokleous,E.;Feng,Z.;Oksanen,E.;Sicard,P.;Wang,Q.;Beier,C.M.;Caputo,J.;Lawrence,G.B.;Sullivan,T.J.2017.LossSaitanis,C.J.;Araminiene,V.;Blande,J.D.;Hayes,F.;Calatayud,ofecosystemservicesduetochronicpollutionofforestsandsurfaceV.;Domingos,M.;Veresoglou,S.D.;Peñuelas,J.;Wardle,D.A.;DewatersintheAdirondackregion(USA).JournalofEnvironmentalMarco,A.;Li,Z.;Harmens,H.;Yuan,X.;Vitale,M.;Paoletti,E.Management.191(2017):19–27.2020.Ozoneaffectsplant,insect,andsoilmicrobialcommunities:athreattoterrestrialecosystemsandbiodiversity.ScienceAdvances.Bennett,A.C.;McDowell,N.G.;Allen,C.D.;Anderson-Teixeira,6(33):eabc1176.K.J.2015.Largertreessuffermostduringdroughtinforestsworldwide.NaturePlants.1(10):15139.https://doi.org/10.1038/Ahmadalipour,A.;Moradkhani,H.;Svoboda,M.2017.Centennialnplants.2015.139.droughtoutlookovertheCONUSusingNASA-NEXdownscaledclimateensemble.InternationalJournalofClimatology.37(5):Bentz,B.J.;Jönsson,A.M.;Schroeder,M.;Weed,A.;Wilcke,R.A.I.;2477–2491.Larsson,K.2019.IpstypographusandDendroctonusponderosaemodelsprojectthermalsuitabilityforintra-andinter-continentalAllen,R.G.;Pereira,L.S.;Raes,D.;Smith,M.1998.Cropestablishmentinachangingclimate.FrontiersinForestsandGlobalevapotraspiration–guidelinesforcomputingcropwaterChange.2:17.requirements.FAOIrrigationandDrainagePaper56.Rome,Italy:FoodandAgricu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e,WashingtonOfficeResearchPrakashNepal,USDAForestService,ForestProductsLaboratory&DevelopmentKarenSchleeweis,USDAForestService,RockyMountainBenjaminPoulter,NASAGoddardSpaceFlightCenter,EarthResearchStationSciencesDivisionKurtRiitters,USDAForestService,SouthernResearchStationSarahAnderson,USDAForestService,WashingtonOfficeForestJeffreyP.Prestemon,USDAForestService,SouthernManagement,RangeManagement,andVegetationEcologyResearchStationEvanB.Brooks,VirginiaTechJ.MorganVarner,TallTimbersResearchStationDavidM.Walker,USDAForestService,SouthernResearchStationthroughOakRidgeInstituteforScienceandEducation2020ResourcesPlanningActAssessment5-55Chapter6ForestResourcesCoulston,JohnW.;Brooks,EvanB.;Butler,BrettJ.;Costanza,JenniferK.;Walker,DavidM.;Domke,GrantM.;Caputo,Jesse;Markowski-Lindsay,Marla;Sass,EmmaM.;Walters,BrianF.;Guo,Jinggang.2023.ForestResources.In:U.S.DepartmentofAgriculture,ForestService.2023.FutureofAmerica’sForestandRangelands:ForestService2020ResourcesPlanningActAssessment.Gen.Tech.Rep.WO-102.Washington,DC:6-1–6-38.Chapter6.https://doi.org/10.2737/WO-GTR-102-Chap6.Sincethe2010ResourcesPlanningAct(RPA)area,volume,andremovalsbasedonU.S.DepartmentofAssessment,theforestsoftheUnitedStateshavebeenAgriculture,ForestServiceForestInventoryandAnalysisaffectedbychangesindisturbancerates,forestmanagement(FIA)data.Thesecondsectioncovershistoricaltrends(includingforestharvestingandplanting),forestownership,inforestownershipbasedonFIA’sNationalWoodlandandlanduse.Atthesametime,forestshavecontinuedtoOwnerSurvey.Thethirdsectionfocusesonprojectionsmatureandprovideasuiteofecosystemservices.Thisofforestarea,volume,andremovals,andexamininghowchaptersummarizesrecentandprojectedtrendsintheforestsocioeconomicandclimatedriversinfluenceprojectedresourcesoftheconterminousUnitedStates.Inthefirsttrends.Thefourthsectionexamineshistoricalandfuturesection,wepresenthistoricalforesttrendswithrespecttotrendsinforestcarbon.KeyFindings❖Importantforesttypesareexpectedtoloseareaduetoforestloss,conversiontoplantedpinefollowingharvest,climate,andsuccession.Theseforesttypesincludeaspen/birchintheNorth,oak/gum/cypressintheSouth,ponderosapineintheRockyMountains,andhemlock/SitkaspruceinthePacificCoastRegion.❖Timberlandgrowingstockvolumeisprojectedtoincreasethrough2050.Post-2050,growingstockvolumetrajectoriesdependonroundwooddemandandlandusechoices.❖Abovegroundbiomasscarbondensity(carbonperunitarea)isprojectedtoincreaseby17to25percentover2020densitiesby2070,whileannualcarbonstockchangeisprojectedtodecrease,indicatingincreasingcarbonsaturationofU.S.forests.TheforestecosystemisprojectedtobecomeanetsourceofCO2by2070underfuturesthatincludehighroundwooddemandandnetforestloss.❖Projectionssuggestthatharvestedwoodcarbonannualstockchangeratesin2070willbegreaterthannetforestecosystemannualstockchangeratesundermoderateandhighgrowthfuturescenarios.❖Althoughforestareaincreased3.6percentbetween1977and2017,forestareaisprojectedtodecreasebetween2020and2070,withnetlossesprimarilydrivenbyconversiontodevelopeduses.❖Thereareanestimated9.6millionfamilyforestownershipsacrosstheUnitedStates,andtheycontrolmoreforestlandthananyotherownershipcategory(39percentexcludinginteriorAlaska).2020ResourcesPlanningActAssessment6-1HistoricalTrendsinU.S.Forests❖Basedon2016estimates,averageharvest❖Forestandtimberlandareaincreased3.6removalsfromtimberlandforproductshavenotrecoveredtopre-recessionlevels.percentfrom1977to2017butshowedsignsofdecreasingfrom2012to2017.ForestLandandTimberlandArea❖Despiteincreasesinforestareafrom1977toIn2017,thetotalforestareaintheUnitedStateswas765millionacres,where514millionacreswasclassifiedas2017,severalforesttypeshavedecreasedintimberland(Oswaltetal.2019).Acrosstheconterminousextent,includinglodgepolepineandponderosaUnitedStates,forestareawas635.3millionacres,anpinetypesintheWesternStatesandaspen/birch,increasefrom612.4millionacresin1977(3.6percent).longleaf/slashpine,andoak/pinetypesintheForestareahasremainedrelativelystableovertime,peakingEasternStates.at635.9millionacresin2012.Mostforestlandistimberland(seethesidebarDefinitions;500.7millionacresin2017,❖Growingstockvolumeontimberlandincreasedor78.8percentofallforestland),andtheshareofforestlandthatistimberlandhasincreasedovertime.Theareaof39percentbetween1977and2017.ThelargestincreasesoccurredintheRPANorthandSouthRegions.DefinitionsAbovegroundbiomass:IntergovernmentalPanelonClimateForestremainingforest:IPCClandusecategorythatChange(IPCC)carbonpoolthattracksalllivingbiomassaccountsforlandthathaspersistedinaforestlanduseoverabovethesoilincludingstem,stump,branches,bark,seeds,anapproximate6-yeartimeperiodintheEasternUnitedandfoliage.Thispoolincludesliveunderstory.Statesanda10-yeartimeperiodintheWesternUnitedStates.ThetimeperiodisdefinedasthedifferencebetweenBelowgroundbiomass:IPCCcarbonpoolthattracksallatime2measurementandatime1.livingbiomassofcoarselivingrootswithdiametersgreaterthan0.08inches(2mm).Growingstock:Alllivetrees5.0inches(12.7centimeters)diameteratbreastheightorlargerthatmeet(noworDeadwood:IPCCcarbonpoolthattracksallnonlivingprospectively)regionalmerchantabilityrequirementswoodybiomasseitherstanding,lyingontheground(notintermsofsaw-loglength,grade,andculldeductions.includinglitter),orinthesoil.Excludesroughandrottenculltrees.Forestconvertedtootherland:IPCClandusecategorythatHarvestedwoodproducts(HWP):IPCCcarbonpoolthataccountsforlandthatwasconvertedfromaforestlanduseattrackscarboninlong-livedwoodproductssuchaspaper,time1toanonforestusebytime2.woodpanels,andsawnwoodthatareinuseandstorecarbonovertheproductslifecycle.Short-livedproducts,Forestland:Landatleast120feet(37meters)wideandsuchaswoodpellets,areconsideredimmediateemissionsatleast1acre(0.4hectare)insizewithatleast10percentofthebiomass.cover(orequivalentstocking)bylivetrees,includinglandthatformerlyhadsuchtreecoverandthatwillbenaturallyLitter:IPCCcarbonpoolthattracksallduff,humus,andorartificiallyregenerated.Treesarewoodyplantshavingafinewoodydebrisabovethemineralsoil,includingwoodymoreorlesserectperennialstem(s)capableofachievingatfragmentswithdiametersofupto7.5centimeters.least3inches(7.6cm)diameteratbreastheight,or5inches(12.7cm)diameteratrootcollar,andaheightof16.4feetMajoreasternforesttypegroups(5meters)atmaturityinsitu.ThedefinitionhereincludesallareasrecentlyhavingsuchconditionsandcurrentlyAspen/birch:Forestsinwhichaspen,balsampoplar,regeneratingorcapableofattainingsuchconditioninthepaperbirch,orgraybirch,singlyorincombination,nearfuture.Forestlandalsoincludestransitionzones,suchcompriseapluralityofthestocking.Commonassociatesasareasbetweenforestandnonforestlandsthathaveatincludemapleandbalsamfir.least10percentcover(orequivalentstocking)withlivetrees,andforestareasadjacenttourbanandbuilt-uplands.Elm/ash/cottonwood:Forestsinwhichelm,ash,orUnimprovedroadsandtrails,streams,andclearingsincottonwood,singlyorincombination,compriseaforestareasareclassifiedasforestiftheyarelessthan120pluralityofthestocking.Commonassociatesincludefeet(37meters)wideoranacre(0.4hectare)insize.willow,sycamore,beech,andmaple.6-2FutureofAmerica’sForestsandRangelandsLoblolly/shortleafpine:Forestsinwhichloblollypine,Douglas-fir:ForestsinwhichDouglas-fircomprisesshortleafpine,orsouthernyellowpines,exceptlongleaforapluralityofthestocking.Commonassociatesincludeslashpine,singlyorincombination,compriseapluralitywesternhemlock,westernredcedar,truefirs,redwood,ofthestocking.Commonassociatesincludeoak,hickory,ponderosapine,andlarch.andgum.Fir/spruce:Forestsinwhichtruefirs,Engelmannspruce,Longleaf/slashpine:ForestsinwhichlongleaforslashorColoradobluespruce,singlyorincombination,pine,singlyorincombination,compriseapluralityofthecompriseapluralityofthestocking.Commonassociatesstocking.Commonassociatesincludeothersouthernpines,includemountainhemlockandlodgepolepine.oak,andgum.Hemlock/Sitkaspruce:ForestsinwhichwesternMaple/beech/birch:Forestsinwhichmaple,beech,orhemlockand/orSitkasprucecompriseapluralityoftheyellowbirch,singlyorincombination,compriseapluralitystocking.CommonassociatesincludeDouglas-fir,silverofthestocking.Commonassociatesincludehemlock,elm,fir,andwesternredcedar.basswood,andwhitepine.Lodgepolepine:ForestsinwhichlodgepolepineOak/gum/cypress:Bottomlandforestsinwhichtupelo,comprisesapluralityofthestocking.Commonassociatesblackgum,sweetgum,oaks,orsoutherncypress,singlyorincludealpinefir,westernwhitepine,Engelmannspruce,incombination,compriseapluralityofthestocking,exceptaspen,andlarch.wherepinescomprise25to50percent,inwhichcasethestandisclassifiedasoak/pine.CommonassociatesincludePonderosapine:Forestsinwhichponderosapinecottonwood,willow,ash,elm,hackberry,andmaple.comprisesapluralityofthestocking.CommonassociatesincludeJeffreypine,sugarpine,limberpine,Arizonapine,Oak/hickory:Forestsinwhichuplandoaksorhickory,Apachepine,Chihuahuapine,Douglas-fir,incensecedar,singlyorincombination,compriseapluralityoftheandwhitefir.stocking,exceptwherepinescomprise25to50percent,inwhichcasethestandisclassifiedasoak/pine.CommonOtherforestland:Reservedforestlandornontimberlandassociatesincludeyellowpoplar,elm,maple,andblackforestswheretheforestlandisnotcapableofproducing20walnut.cubicfeetperacreperyearofvolume.Oak/pine:Forestsinwhichhardwoods(usuallyuplandOtherlandconvertedtoforest:IPCClandusecategoryoaks)compriseapluralityofthestocking,butinwhichthataccountsforlandthatwasconvertedfromanonforestpineoreasternredcedarcomprises25to50percentoftheuseattime1toaforestuseattime2.stocking.Commonassociatesincludegum,hickory,andyellowpoplar.Parcelization:Thedivisionoflargerparcelsofland,typicallyownedbyasingleentity,person,orfamily,intoSpruce/fir:Forestsinwhichspruceortruefirs,singlysmallerparcelswithmultipleowners.orincombination,compriseapluralityofthestocking.Commonassociatesincludewhitecedar,tamarack,maple,Reservedforestland:Forestlandwithdrawnfromtimberbirch,andhemlock.utilizationthroughstatute,administrativeregulation,ordesignationwithoutregardtoproductivestatus.White/red/Jackpine:Forestsinwhicheasternwhitepine,redpine,orjackpine,singlyorincombination,SoilorganicC(SOC):IPCCcarbonpoolthattracksallcompriseapluralityofthestocking.Commonassociatesorganicmaterialinsoiltoadepthof1meterbutexcludestheincludehemlock,aspen,birch,andmaple.coarserootsofthebelowgroundpools.MajorwesternforesttypegroupsSolidwastedisposalsite(SWDS):IPCCcarbonpoolthattracksHWPcarbonbyproductandenduseonceithasbeenCaliforniamixedconifergroup:acomplexassociationdisposedof.ofponderosapine,sugarpine,Douglas-fir,whitefir,redfir,andincensecedar.Generally,fiveorsixconiferspeciesTimberland:Forestlandthatisproducingorcapableofareintermixed,eitherassingletreesorinsmallgroups.producing20cubicfeetperacreperyearormoreofwoodatMixedconifersitesareoftenoneast-facingslopesoftheculminationofmeanannualincrement.TimberlandexcludesCaliforniaCoastRangeandonthewest-facingandhigherreservedforestlands.elevationeast-facingslopesoftheOregonCascadesandSierraNevadas.2020ResourcesPlanningActAssessment6-3timberlandincreasedby29millionacresfrom1977to2017area:loblolly/shortleaf(51percent),Douglas/fir(12percent),(6.1percent),whiletheareaofotherforestlanddecreasedlongleaf/slashpine(11percent),white/red/jackpine(5by6.1millionacres(4.3percent).percent),andponderosapine(2percent).ChangesinforestlandandtimberlandareavariedacrossTimberlandAreabyForestTypeGrouptheconterminousUnitedStates(figure6-1).TheareaofforestlandintheRPANorth,South,andRockyMountainTimberlandsacrosstheconterminousUnitedStatesRegionsincreasedfrom1977to2017,whileforestlandareaexperiencechangesinarealextent,foresttypecomposition,decreasedinthePacificCoastRegion.TheNorthRegionandstandorigin.Shiftsintheseattributesaredrivenbysawthelargestgain,increasingfrom164.2millionacreslandusechange,investmentinplantationforestry,forestto175.8millionacres(againof11.6millionacres,or7.1succession,anddisturbance.Thecurrentdistributionofpercentofthe1977area),followedbytheSouthandRockytimberlandforesttypegroups(FTGs)isaresultoftheseMountainRegions,whichgained10.1and3.4millionacres,drivers(seethesidebarDefinitionsforadescriptionofmajorrespectively(4.3and2.7percent,respectively).Incontrast,easternandwesternforesttypegroups).EightFTGssawathePacificCoastRegionlost2.3millionacres(2.6percent).netincreaseintimberlandareafrom1977to2017,rangingThethreeRPAregionsthatgainedoverallforestareafromfrom2.4millionacres(fir/spruce/mountainhemlock)to1977to2017alsogainedtimberland,whilethePacificCoast16.7millionacres(oak/hickory)(figure6-2).ThemostRegionlosttimberland.TheoveralllossofotherforestlandwidespreadFTGsintheEasternUnitedStates—oak/hickory,acrosstheUnitedStatescamefrommoderatetolargelossesmaple/beech/birch,andloblolly/shortleafpine—allgainedinthetwowesternregions,whileotherforestlandincreasedsubstantialareasoftimberlandoverthattime.Theloblolly/inthetwoeasternregions.shortleafpineforesttypegroupincreasedinareaduetoagriculturalabandonment(naturalseedingandgrowth)Figure6-1.AreaofforestlandbyRPAregionfortheconterminousUnitedandtreeplantingforcommercialorconservationpurposesStates,1977to2017.Timberlandisdistinguishedfromotherforestlanduses.(SouthandHarper2016,WearandGreis2013).TheDouglas-firandfir/spruce/mountainhemlocktypegroups,Millionsofacres250whicharerelativelywidespreadintheWesternUnited200States,alsoincreasedinareafrom1977to2017.1501990200020101980199020002010100YearTwelveFTGslosttimberlandareafrom1977to2017,rangingfrom-0.4millionacres(westernwhitepine)to-6.850millionacres(oak/pine)(figure6-2).SeveralwesternFTGs0dominatedbypinespecieslostarea,includingtheponderosapine,lodgepolepine,andwesternwhitepinegroups.Many250ofthoseFTGshavebeensubjecttoaseriesofinteracting200disturbancessinceatleasttheearly20thcentury,including150firesuppressionandmountainpinebeetle,whichhave100resultedindecreasedextentofthoseforests(Stankeetal.2021).Inaddition,increasesinbackgroundmortalityhave50beendocumentedinmanywesterntreespecies,withpines0showingthegreatestratessincethe1990s(VanMantgemetal.19802009).ThewesternwhitepineFTGlostthemostarearelativetoitssmall1977range(78percentloss,from0.5millionacresOtherforestlandTimberlandin1977to0.1millionacresin2017),havingfacedthreatsfromwhitepineblisterrustinadditiontoareareductionsPlantedForestduetofireandbeetles(Dudneyetal.2020,Schwandtetal.2010).Theaspen/birchFTG,distributedintheRPANorthandPlantedforestsrepresentsomeofthemostactivelymanagedRockyMountainRegions,alsoshowedarelativelysubstantialtimberlandintheUnitedStates.Forestsareplantedtomeetdeclineinarea.Recentdeclineandmortalityofaspenforestsmanagementobjectives,includingrestorationandsupplyinghasbeenlinkedtowarminganddryingclimate(Hannaandroundwoodforforestproducts(Oswaltetal.2019).RoughlyKulakowski2012,Rehfeldtetal.2009).13percent(68millionacres)oftimberlandshowedevidenceofplantingin2017.MostplantedtimberlandisintheRPAThreeforesttypegroupsthatarerelativelywidespreadinSouthRegion(71percent),followedbythePacificCoasttheEasternUnitedStateshavedeclinedinareaovertheRegion(19percent),NorthRegion(9percent),andRockypast40years:longleaf/slashpine,oak/gum/cypress,andMountainRegion(1percent).Oftheplantedtimberland,oak/pine.Forestsdominatedbylongleafpinedeclinedthereareseveralcommerciallyimportantforesttypegroups(FTGs)thatmakeuparelativelylargeshareoftotalplanted6-4FutureofAmerica’sForestsandRangelandsFigure6-2.Netchangestotimberlandarealextentfrom1977to2017forforesttypegroupsintheEastandWest.OnlyFTGswithavailablehistoricalinformationwereincluded.FTG=foresttypegroup.inareaovermuchofthe20thcenturyduetohistoricfireasgeneralforesthealthandproductivity.Timberlandsuppression,landuseconversion,andconversiontoothervolumeincreasedacrosstheconterminousUnitedStatesforesttypegroupslikeloblolly/shortleafpine(Oswaltetfrom1977to2017,from680.4billioncubicfeetto947al.2014).Whiletheareaoflongleafpineforestsstartedbillioncubicfeet(39.2percent).Thevolumeincrease,onatoincreaseinthe1990s,ithasnotreachedpreviouspercentagebasis,wasroughly10timesgreaterthanforestlevels(Oswaltetal.2014,SouthandHarper2016).Theareaincrease(percentagebasis)overthesameperiod.BothAmerica’sLongleafRestorationInitiativesetagoaltohardwoodandsoftwoodtimberlandvolumesincreased,doubletheareaoflongleafpinebetween2009and2025.by158.6billioncubicfeet(60.6percent)and108billionBasedonMcIntyreetal.(2018),gainsinlongleafpinecubicfeet(25.8percent)respectively.Theannualnetareahavebeenoffsetbylossesleadingtorelativelystablechangeintimberlandvolumeaveraged+6.7billioncubiclongleafpineareafrom2010to2016.However,slashpinefeetperyearfrom1977to2017;however,netchangeinforestshavecontinuedtodeclineinarea(Oswaltetal.timberlandvolumevariedbyregion(figure6-3).Robust2014).LandconversionandlackoffloodinghaveledtogrowthintheEastfrom1977to2017ledtoincreaseddecreasedextentofbottomlandhardwoodforests(Mitchelltimberlandvolume.Specifically,timberlandvolumesintheetal.2009)suchasthosefoundintheoak/gum/cypressNorthandSouthRegionsincreased107billioncubicfeetFTG.Thedeclineinareaofoak/pineforests,distributed(65.7percent)and95.7billioncubicfeet(42.8percent),primarilyintheRPASouthRegion,isduetolanduserespectively.IntheWest,increasesintimberlandvolumechange,successiontooak/hickoryforest,andconversiontowerelesspronounced:thePacificCoastRegionincreasedloblolly/shortleaftypes.by35.1billioncubicfeetandRockyMountainRegionincreasedby28.8billioncubicfeetfrom1977to2017.GrowingStockVolumeOverthelastdecade(2007to2017)growingstockvolumeontimberlandwasrelativelystaticintheWest,whilevolumeThegrowingstockvolumeontimberland(“timberlandintheEastcontinuedtogrow.volume”)isakeystructuralcomponentofU.S.forests.TimberlandvolumetrendsprovideinsightintothepotentialVolumetrendsfrom1977to2017differedbyspeciesamountofwoodavailableforforestproducts,aswell(hardwoodversussoftwood)andRPAregion.IntheNorthand2020ResourcesPlanningActAssessment6-5Figure6-3.GrowingstockvolumesbyRPAregionfrom1977to2017,by(figure6-4).By2016,totalremovalsfromthePacificCoasthardwood/softwood.RegiondecreasedtolevelscomparablewiththeNorthRegion(17.3percentofremovalsin2016camefromthe300BillionsofcubicfeetPacificCoast,comparedto19.2percentfromtheNorth).200BillionsofcubicfeetperyearHardwoodandsoftwoodremovalsdifferedbetweenthe100tworegions,with73.8percenthardwoodremovalsfortheNorthcomparedto96.4percentsoftwoodremovalsforthe0PacificCoast.TheRockyMountainRegionmaintainedthelowestremovalratesofallregions,withitsshareof3001990200020101980199020002010removalsdecreasingfrom6.4percentto3.1percentfrom200Year1976to2016.100Figure6-4.AverageannualgrowingstockremovalsbyRPAregionfrom01976to2016,byhardwood/softwood.198010.0HardwoodSoftwood7.55.0SouthRegions,hardwoodspeciesmadeup84.3percent(90.32.5billioncubicfeet)and58.1percent(55.6billioncubicfeet)oftheincreasedtimberlandvolume,respectively.Incontrast,0.0theincreasedtimberlandvolumeintheRockyMountainandPacificCoastRegionswasprimarilyfromsoftwood10.0species:83.4percent(24billioncubicfeet)and77.5percent(27.2billioncubicfeet),respectively.Whileallfourregions7.5experiencednetincreasestotimberlandvolumefrom1977to2017,theRockyMountainRegionexperiencedatimberland5.0volumepeakin2007of137.3billioncubicfeetbeforedecreasingto130billioncubicfeetin2017.Timberland2.5volumeintheconterminousUnitedStatesgenerallyincreased,primarilyduetoforestgrowthandaslightincreaseinoverall0.0timberlandarea.1976198619962006201619761986199620062016GrowingStockRemovalsYearRemovaloftimberlandgrowingstockisdrivenbysocietalneedsforforestproductsandlandusechange.AnnualHardwoodSoftwoodremovalsincreasedthroughthe1980sand1990s,withpeakannualremovalsof15.9billioncubicfeetoccurringAgeDynamicsin1996.By2016,annualremovalshaddecreasedtovolumeslowerthan1976(13billioncubicfeetin2016Standageisanimportantindicatorofforeststructurecomparedto14.1billioncubicfeetfor1976).However,becausekeystructuralparameterssuchasvolume,biomass,basedonOswaltetal.(2019),2016annualremovalsbasalarea,andheightarecorrelatedwithstandage.Mostwerehigherthanthoseobservedduringthe2007to2009traditionaleven-agedmanagementanalyses(e.g.,growthrecession,whichdroveannualremovalsdownacrosstheandyieldcurves,siteindex)directlyincorporatestandconterminousUnitedStates(Hodgesetal.2012,Woodalletagebecauseofthiscorrelation.Whiletheinterpretational.2012).ofstandageinuneven-agedstandsislessclear,standageremainscorrelatedwithstructuralstandparameters,andMostremovalsoccurredintheSouthforbothhardwoodsmanyinventoryprojectionmodelsdependonstandageandsoftwoods(asharethatincreasedfrom47.3percentinformationandassumptionsaboutagetransitions(seeWearto60.4percentofremovalsfrom1976to2016),withtheandCoulston2019forasummary).increaseinsoftwoodremovalsthereoffsettingthedecreaseinsoftwoodremovalsfromthePacificCoastRegionStandage,asmeasuredbytheFIAprogram,istheaverageageofthreedominantorcodominanttreesinthestand.Agetransitionsoccurnaturallyovertimeandareinfluencedbyforestmanagementandtreatments.ThetypeanddegreeofanagetransitionbetweentwopointsintimecanbeestimatedusingremeasuredFIAfieldinventoryplots.Age6-6FutureofAmerica’sForestsandRangelandstendstoprogresslinearlyovertimeforundisturbedstands;TrendsinForestOwnershiphowever,aportionofundisturbedstandsdecreaseinageovertimewhenthedominantorco-dominantcohortoftrees❖Nationally,60percentofU.S.forestlandisreplacedbyayoungercohort.Clear-cutharvestingandstandclearingdisturbanceareage-resettingevents.Partial(excludinginteriorAlaska)isprivatelyowned,38cuttingandotherdisturbancescouldaffectstandage:therepercentispubliclyowned,and2percentiswithinisnoeffectonageiftheoriginalcohortoftreesremainTribalreservationboundaries(Butleretal.2021a).dominantorco-dominantbutstandagewillbereducedbysomeamountifayoungercohortoftreesbecomesdominant❖Therelativedistributionsofforestlandbybroadorco-dominantfollowingthedisturbance.Mostdisturbedstandscontinuetoagelinearlywithtime.TheagetransitionownershipcategorieshaveshownageneraltrendprobabilitiesestimatedfromtheFIAdatasuggestthattheofincreasingpublicownershipoverthepast60+ageclassdistributionwillshifttoolderstandsovertime,years,butthepatternappearstohavestabilizedevenwithdisturbanceandmanagementannuallyaffectingaoverthelastdecade.portionoftheforestland.❖Withintheprivateownershipcategory,timberlandFigure6-5showstheforestagedistributionsbasedonthetwomostcurrentmeasurementsoftheFIAinventory.Ininvestmentmanagementorganizations(TIMOs)theEasternUnitedStates,theforestareainageclassesandrealestateinvestmenttrusts(REITs)haveyoungerthan60yearsdecreasedbetweentime1andtimeincreasedinimportanceoverthepastfew2measurements,andtherewasacorrespondingincreaseindecades.forestgreaterthan60yearsold.Evenwithdisturbanceandharvesting,theeasternforestsareaging.IntheWest,there❖Thereareanestimated9.6millionfamilyforestwasgenerallyanincreaseinforestareaforageclasseslessthan30years,followedbyadecreaseinforestareaforageownershipsacrossthecountryandtheycontrolclassesfrom40to80years,andanincreaseintheextentmoreforestlandthananyotherownershipofforestgreaterthan100yearsold.Thedecreasein40-tocategory(39percent,excludinginteriorAlaska),80-year-oldforestswasaresultofdisturbancessuchasfirebutmostdonothaveawrittenforestmanagementandinsects,aswellasforestharvesting.planandhavenotreceivedforestmanagementadvice.Landowners,operatingwithinthesocial,political,economic,andecologicalenvironments,ultimatelydecidehowlandwillbeusedandwhowilldirectlybenefitfromit.Thesetoflaws,regulations,andsocialnormsthatcontrolwhatFigure6-5.ForestageclassdistributionfortheEastern(left)andWestern(right)conterminousUnitedStatesbasedonthemostcurrenttwomeasurementsperforestplotoftheforestinventory.EastWestTime1Time22020ResourcesPlanningActAssessment6-7apersonororganizationcanandcannotdowithagivenmoreforestlandthananyotherownershipgroup.OverhalfpieceoflandanditsassociatedresourcesarecalledlandoftheforestlandintheSouthandNorthRegionsisownedtenurerights.TheUnitedStateshasstrongandwell-definedbymillionsoffamilyforestowners(56percentand52landtenurerightsthathelpdeterminetheexclusivity,percent,respectively).IntheRockyMountainandPacifictransferability,alienability,andenforceabilityassociatedCoastRegions,however,67percentand57percentofforestwiththeresources.Theserightsmayvarydependingontheland,respectively,isfederallyowned,withmuchundertheresourcebeingconsidered(e.g.,treesversusbelow-groundjurisdictionoftheUSDAForestServiceandtheU.S.Bureauminerals),locationintheUnitedStates(e.g.,riparianwaterofLandManagement.ThehighestpercentageofTribalrightsinmostEasternStatesversuspriorappropriationwaterlandisintheRockyMountainRegion(8percent),withtherightsinmostWesternStates),andownershiptype(e.g.,NavajoNationmanagingapluralityoftheTribalforestlandpublicversusprivateversusTribalownership).areaintheregion.Ownershipsarediverseintermsoflegalstructures,OwnershipDynamicsownershipobjectives,sizeofholdings,awarenessofopportunitiesandthreats,andabilitiestotakeadvantageofTherelativedistributionsofforestlandoverthepast60+yearsopportunities.Ownershippatternsconsistofapatchworkhaveshownageneraltrendofincreasingpublicownership,ofdifferentownerships,whichvaryacrossthecountryandbutthepatternappearstohavestabilizedoverthelastdecadecanchangeaslandsareboughtandsoldortheownership(figure6-7;Oswaltetal.2019).Thetrendwasaresultofstructuresandobjectivesshift.Patternsandtrendsinlandsomeprivatelandsbeingtransferredtopublicownershipacquisition/disposal,landuseconversion,andharvesting(particularlyState),aswellasthelossofprivateforestlandtoimpactthecurrentstateofAmerica’sforestsandwillnonforestuses,includingagricultureanddevelopment.continuetoshapeitsfuture.TheemergenceoftimberlandinvestmentmanagementForestOwnershipPatternsorganizations(TIMOs)andrealestateinvestmenttrusts(REITs)overthepastfewdecadeshaschangedforestNationally,60percentoftheforestland,excludinginteriorAlaskaduetodatalimitations,isprivatelyowned,38Figure6-7.PrivateandpublictimberlandownershipbyRPAregionandforpercentispubliclyowned,and2percentiswithinTribaltheconterminousUnitedStates.reservationboundaries(Butleretal.2021a).However,theseownershippatternsvarysubstantiallyacrossthecountry(figure6-6).Familyforestownerships(i.e.,individuals,families,trusts,estates,andfamilypartnerships)controlFigure6-6.ForestownershipacrosstheconterminousUnitedStatesin2017.REIT=realestateinvestmenttrusts;TIMO=timberlandinvestmentmanagementorganization.Historicaldataareonlyavailablefortimberlands.Triballandsareincludedwithprivateownerships.Source:Sassetal.2020.Source:Oswaltetal.2019.6-8FutureofAmerica’sForestsandRangelandsownershipintheUnitedStates.Thishistoricrestructuringownershipcategories,particularlyontheprivateside,butwastheresultofchangesinFederalpolicy,changesinweareunabletofullyquantifythosetransactionsgivenexpectationsofinvestorsinverticallyintegratedforestrycurrentlyavailabledata—theincreasingprevalenceofcompanies,andopportunitiesfornewinvestments(BinkleyTIMOsandREITswithinthecorporatecategorybeingaetal.1996,ButlerandWear2013).TIMOsandREITsnowprimeexample.representalargepercentageoftheNation’scorporateforestland,collectivelycontrollinganestimated41millionacres,FamilyForestOwnershipsandhaveacommensuratelyimportantroleintheprovisionoftimberandotherresources.Thereareanestimated9.6millionfamilyforestownershipsacrosstheUnitedStates,andtheycontrolmoreforestlandThelargestnetchangesacrossownershipgroupsoverthethananyotherownershipcategory(39percentexcludingpastdecadehavebeenanincreaseincorporateforestlandinteriorAlaska).TheUSDAForestServiceconductstheanddecreasesinfamilyandFederalforestland(figure6-8;NationalWoodlandOwnerSurveytobetterunderstandSassetal.2021).Mostoftheincreaseincorporateforesttheattitudes,behaviors,andothercharacteristicsofthislandhascomefromfamilyforestlands.Althoughtheimportantgroupofowners(Butleretal.2021a).detailsareunknown,itisassumedthatthistransferisduetoacombinationoftraditionalcorporationsacquiringnewAnimportantattributeoffamilyforestownershipsissizeoflandsandfromfamilyforestownershipsconvertingtheirholdings.Thisattributedirectlyimpactssomeactivitiesdueownershipstocorporatestructuresfortax,inheritance,andtoeconomiesofscale,suchasthehighercostsofharvestingotherreasons.Sometrends(e.g.,Federallandstransitioningtimberonsmallerparcels,andisindirectlycorrelatedwithtononforest)arelikelyassociatedwithchangesinthemanyotherattributes(Butleretal.2021b).Whilemostestimatedproductivityofforestlandgrowinginincreasinglyfamilyforestownershaverelativelysmallforestholdingsharshenvironments.Ownershiptransfersalsooccurwithin(i.e.,62percentofthefamilyforestownershipsownlessFigure6-8.Forestlandgainandlossbyownershipgroupbetween2007and2017.Source:Sassetal.2021.2020ResourcesPlanningActAssessment6-9than10acres),mostofthefamilyforestacreageoccursFigure6-10.Percentageoffamilyforestacreageandfamilyforestownershipwithinlargeholdings(i.e.,58percentofthefamilyforestbyownershipobjectivesin2018.Errorbarsare95percentconfidencelandisinholdingsofatleast100acres;figure6-9).Theintervals.averagesizeoffamilyforestholdingsin2018was28acres(or69acres,ifonlylookingatfamilyforestownershipsofmorethan10acres);thesevaluesarenotsubstantiallydifferentfrom2013(Butleretal.2016).Theobjectivesoffamilyforestlandownershavenotchangedappreciablysincethefirstnationallandownersurveyswereconductedinthe1990s(Birch1996).Familyforestownersciteamenityvalues—includingaesthetics,natureprotection,andwildlife—astheprimaryreasonforowningforestland(figure6-10).Intermsoffinancialobjectives,landinvestmentisimportantforownersof58percentofthefamilyforestland,andtimberproductionisimportantfor34percent.Formanyoftheremainingfamilyforestowners,theirforestsaremeetingtheirneedsandarelargely“runninginthebackground”(Kittredge2004).Whileanestimated48percentofthefamilyforestlandisownedbypeoplewhohavecommerciallyharvestedtrees,thefactthatFigure6-9.Percentageoffamilyforestownershipsandfamilyforestacreagebysizeofforestholdingsin2013and2018.Errorbarsare95percentconfidenceintervals.AcresOwnershipsNTFPs=nontimberforestproducts.Ownersthatidentifiedanobjectiveasimportantorveryimportantona5-pointLikertscaleareincludedinpercentages.Source:Butleretal.2021a.2013201823percentofthefamilyforestlandisownedbypeoplewhohaveawrittenforestmanagementplanand34percentbySource:Butleretal.2016,2021a.peoplewhohavereceivedforestmanagementadviceintheprevious5yearssuggeststhatmanyharvestsareunplanned.Effortstailoredtotheowners’concerns,includingpropertytaxes,keepinglandintactforfuturegenerations,trespassing/vandalism,andotherself-identifiedissues,inadditiontotheconcernsidentifiedbynaturalresourceprofessionals,couldencouragegreaterinterestandparticipationinforestmanagementassistanceprogramsandservices(figure6-11).Demographicsareimportantforunderstandingfamilyforestownershiptrends.Giventhattheageoftheprimaryfamilyforestdecisionmakeris65orolderfor56percentofthefamilyforestland,intergenerationaltransferhasthe6-10FutureofAmerica’sForestsandRangelandsFigure6-11.PercentageoffamilyforestacreageandfamilyforestownershipsFigure6-12.Familyforestacreageandfamilyforestownershipdemographicsidentifyingpotentialownershipconcernsin2018.Errorbarsare95percentin2018.Errorbarsare95percentconfidenceintervals.confidenceintervals.AcresOwnershipsSource:Butleretal.2021a.AcresOwnershipsFigure6-13.Percentageoflargecorporateforestownershipsbyownershipobjectivesin2018.Errorbarsare95percentconfidenceintervals.Ownersthatidentifiedanissueasaconcernorgreatconcernona5-pointLikertscaleareincludedinpercentages.Source:Butleretal.2021a.potentialtosignificantlyimpactfutureownershipdynamicsNTFPs=nontimberforestproducts.(figure6-12).AlthoughmostoftheprimarydecisionmakersOwnersthatidentifiedanobjectiveasimportantorveryimportantona5-pointLikertscalearearemale,weknowthatmostfamilyforestsareownedbyincludedinpercentages.amarriedcouple.NonwhitelandownerscompriseamuchSource:Butleretal.2021a.smallerpercentageofthefamilyforestpopulationthanthegeneralU.S.population.Nonwhitelandownershavebeenshowntoparticipateinprogramsatlowerrates(Butleretal.2020)andfacesomechallengesnotencounteredbywhitelandowners(Hitchneretal.2017).CorporateForestOwnershipsForlarge,corporateforestlandowners,theprimaryreasonsreportedforowningforestlandincludetimberproduction,landinvestment,andtheprotectionofwaterresources,aligningwiththeirbusinessmodels(figure6-13).Largecorporateownerships—thosethatownmorethan45,000acres—aremorelikelytohaveformalmanagement2020ResourcesPlanningActAssessment6-11structuresthanfamilyforestowners:approximatelythreeProjectedFuturesofU.S.Forestsquartersoflargecorporationsreporthavingawrittenmanagementplanthatcoversalloftheirland.Certification,❖ForestareaintheconterminousUnitedStatessuchasthroughtheSustainableForestryInitiativeandForestStewardshipCouncil,andconservationeasementsareisprojectedtodecreasefrom634millionacresalsorelativelycommon,withtwo-thirdsofcompaniesandtobetween619and627millionacresin2070.halfofcompaniesreportingeachitem,respectively(SassetNetlossesareprimarilydrivenbyconversiontoal.2021).Corporateownersmostcommonlyreportconcernsdevelopeduses.relatingtoregulationsandchangestotaxesandmarkets,butbiologicalandenvironmentalissues,includinginsects,❖Importantforesttypegroupsareexpectedtolosedisease,invasiveplants,andwildfire,arealsoconcerningtoamajorityofcompanies(figure6-14).Largecorporateareaduetotheinteractionofforestloss,harvest,forestlandownerships,includingTIMOsandREITs,reportclimate,andsuccession.Thesetypegroupshighlevelsofengagementwiththemanagementoftheirincludeaspen/birchintheRPANorthRegion,oak/forestlandtomeettheirfinancialgoals.gum/cypressintheSouth,ponderosapineintheRockyMountains,andhemlock/SitkaspruceinFigure6-14.PercentageoflargecorporateforestownershipsidentifyingthePacificCoast.potentialownershipconcernsin2018.Errorbarsare95percentconfidenceintervals.❖TimberlandgrowingstockvolumeisprojectedtoOwnersthatidentifiedapotentialconcernasaconcernorgreatconcernona5-pointLikertscaleincreasethrough2050,buttrajectoriesafter2050areincludedinthepercentages.dependonroundwooddemand.RPAscenariosSource:Sassetal.2021.withhighroundwooddemand(LMandHH)leadtodecreasesingrowingstockvolumepost-2050.❖Hardwoodgrowingstockvolumeisprojectedtoincreaseoverthe2020to2070projectionperiod,whilesoftwoodgrowingstockvolumeisprojectedtodecreasepost-2050.Themagnitudeofthedecreasedependsondemandforsoftwoodroundwood.❖AcrossRPAscenarios,removalsforroundwoodproductsareexpectedtoincreasefrom2020levels.Softwoodremovalsareexpectedtoincreasemorethanhardwoodremovals.Forestdevelopmentisdrivenbyasuiteofbiological,edaphic,climate,management,andlandusechoicesthatnotonlydetermineforestfunctionbutalsoinfluencetheecosystemservicesarisingfromtheforestsoftheUnitedStates.TheprojectedfuturesofU.S.forestsarebasedontheForestDynamicsModel(seethesidebarForestDynamicsModelformoreinformation)whichincorporatesinformationfromthecounty-levellandusechangemodel(seetheLandResourcesChapter)andisharmonizedwiththeglobaltrademodel(FOROM)describedintheForestProductsChapter.TheForestDynamicsModelprojectstheFIAinventoryforwardasinfluencedbybiological,physical,climatic,andhumanfactorsthatalterexpectedfutures.HerewesummarizeresultsfromtheForestDynamicsModelforthefourRPAscenariosorthe20RPAscenario-climatefuturesdescribedinthesidebarRPAScenarios.IncaseswhereonlyRPAscenarioresultsarepresented,thoseresultsarebasedonaveragingdecadalresultsacrossthefiveclimateprojectionsevaluatedwithineachRPAscenario.6-12FutureofAmerica’sForestsandRangelandsForestDynamicsModelModelOverview(figure6-15);theMatchthenProjecttechniqueisusedintheEasternUnitedStateswhereeachinventoryplotTheForestDynamicsModelisastochasticmodelinghastwoorthreemeasurements.Inbothcases,theoverallsystemwhichprojectstheFIAdatabaseattheplotapproachistocurateapoolofdonorplotsforatarget(condition)levelusinganimputationapproach(Coulstonplot,usingtheFIAdatabasebasedoncurrent(time1)andetal.inpreparation).Thisapproachallowsforconsistentpredicted(time2)plotstates,thenselectrandomlyfromprojectionsacrossarangeofvariablesofinterest(e.g.,thatpooltoupdatethetargetplot.volume,age,carbon,foresttype)whilemaintainingtheobservedrelationshipsamongFIAvariablesattheplotTheforestedlandusechangecomponentsoftheForestlevelthroughtheprojectionperiod.ThemodelingsystemDynamicsModelarisefromthecounty-levelgrosslanduseisinformedbyexogenousvariablessuchasclimate,changeprojectionsdiscussedintheLandResourcesChaptertimberprices,population,andincome;thesystemis(MihiarandLewis2021).TheFIAexpansionfactors,alsoinformedbyasetofstatetransitionsubmodelsderivedfromtheareasamplingframe,areadjustedtoreflectrepresentinglandusechange,harvestchoices,forestbothforestareagainsandforestarealosses.Twoseparatedisturbance,growth,aging,regeneration,andforesttypesubmodelsareusedtoaccountfordifferencesintheforesttransitionsovertime.types,plantingstatus,andstructuralcharacteristics(e.g.,age,volume)ofplotsexperiencinggainsorlosses.Twodifferentimputationtechniquesareused,dependingontheavailabilityofremeasuredFIAplotdata.TheTheForestDynamicsModelisharmonizedwiththeProjectthenMatchtechniqueisusedintheWesternGlobalTradeModel(FOROM),discussedintheForestUnitedStates,whereremeasuredplotdataarelimitedProductsChapter.WhensolvingforglobalforestsectorFigure6-15.ImputationapproachesusedintheForestDynamicsModel.Predictedstatesarederivedfromasetofstateexogenousvariablesandtransitionmodels.Notethattheprimarydifferencebetweenthetwoapproachesrelatestobasalarea(BA),standage(Age),andforesttype.IntheProjectthenMatchapproachmodelsareusedtopredictthestateofthosevariablesattimet+n.IntheMatchthenProjectapproachpredictionsofBA,Age,andforesttypearenotneededsincethematchingoccursattimetforthesevariables.Bothapproachesrelyonthepredictedprobabilitiesofharvest,disturbance,andforestplanting(regeneration)afterharvestattimet+n.Climateprojectionsattimet+nalsoinformthemodelingsystem.ProjectthenMatchMatchthenProject(WesternUnitedStates)(EasternUnitedStates)2020ResourcesPlanningActAssessment6-13solutionsinFOROM,climate-inducedproductivityofadonorplot.Thestatetransitionmodelsforharvest,changeprojectionsmadebyMC2fortheUnitedStatesregeneration,disturbance,andforesttypeareprobabilistic;werereplacedbythosemadebytheForestDynamicsforexample,thedesignationofaplottobeharvestedModel.ProjectionsoftheU.S.forestsectormadeisdrawnrandomlyfromthepoolofdonorplotswithjointlywithFOROMandtheForestDynamicsModelprobabilityproportionaltothemodelprediction.Theforestwereharmonizedoninventory(volume)andremovalslossandforestgainmodelsarealsoprobabilistic,where(roundwoodproduction)tofindaroundwoodpricepathforestgainsaredistributedacrossplotsbasedontheplot-wheretheinventoryandremovalsfortheUnitedStateslevelprobabilityofafforestationandsimilarlyforforestalignedovertheprojectionperiod.Ineach5-yeartimelosses.Thegroupsofsimilardonorplots(bins)haveatstepofFOROM,theForestDynamicsModelwasusedtoleast20donorplotsineachbin.ThedonorforeachplotiscalibrateinventorygrowthratesacrosstheRPAregionsandselectedrandomlywithreplacement.wereanexogenousinputintoFOROM.Then,FOROMprojectedanendogenouspathofremovalsandroundwoodImplementationprices.TheroundwoodpriceswerethenusedintheForestDynamicsModelharvestchoiceandtimbersupplymodelsForeachofthe20RPAscenario-climatefutures,theFIAtoprojectremovals.TheprojectedremovalsfromFOROMinventoryisprojectedforwardinapproximate5-yeartimeandtheForestDynamicsModelwerethencomparedtostepsfortheEasternUnitedStatesand10-yeartimestepsensurealignment.BecausetheForestDynamicsModelfortheWesternUnitedStates.ThesetwodifferenttimeusedboththeRPAscenariosandtheindividualclimatesteplengthsarebasedonthedifferingFIAinventorycyclemodelprojections(leastwarm,hot,dry,wet,middle),thelengths.ForeachtimestepandRPAscenario-climateharmonizationwasperformedforeachRPAscenariowherefuture,100realizationsoftheFIAinventoryareproduced.ForestDynamicsModelinventoryandremovalswereEachprojectedinventoryissummarizedbasedonstandardaveragedacrossclimateprojectionsforeachtime-stepintheFIAprotocolsdescribedinBurrilletal.2018.FortheForestprojectionperiod.ResourcesChapter,projectedforestparametersbytimestep/decadearegiveneither:(1)astheaverageacrosstheAsnotedearlier,theForestDynamicsmodelingsystemis100realizationswithineachRPAscenario-climatefuturestochastic.Randomnessentersthesysteminthreeplaces:(fourscenariosxfiveclimateprojections),or(2)asthe(1)inthestatetransitionmodelsforharvest,regeneration,averageacrossthe500realizations(fiveclimateprojectionsdisturbance,andforesttype;(2)inthemodelsaccountingx100realizations)withineachRPAscenario.forforestlossandforestgains;and(3)intheselectionForestLandandTimberlandAreaprivateland(seetheLandResourcesChapter).ThetotalforestareaacrosstheconterminousUnitedStateswas634millionTheamountandqualityofservicesprovidedbyU.S.forestsacresin2020,butitisprojectedtodecreaseacrossallRPAaredirectlyrelatedtothetotalamountofforestland,inscenario-climatefutures(seetheLandResourcesChapter,additiontoforestconditions,forestfragmentation,foresttable4-9)tobetween619millionacres(15millionacrelossownership,andforestparcelization.TheU.S.forestlandbaseundertheHH-leastwarmRPAscenario-climatefuture)andisdefineddifferentlydependingonthespecificservicesbeing627millionacres(7.6millionacreloss,HL-hot).Forestexamined(Nelsonetal.2020).Forexample,thearealextentareaprojectionsaremoresensitivetoRPAscenariosthantooftimberlandistypicallyusedwhenquantifyingtimberandspecificclimateprojections,andtheSouthandPacificCoastremovalvolumes,whiletheforestcarbonlandbaseisusedtoRegionsareprojectedtolosethelargestamountsofforestquantifyCstocksandstockchanges.Theprojectedchangesarea.TheLandResourcesChaptergivesafulldiscussionofinforest,timberland,andforestClandbasesaredrivenbygrossandnetlandusechangeforforests,inadditiontothetheRPAcountylandusechangemodel,whichreflectsbothotherprimarylanduses.netandgrosslandusechangetoprivatelandsacrosstheconterminousUnitedStates(seetheLandResourcesChapter).In2020,78.5percent(498millionacres)oftheforestlandTheresultspresentedintheLandResourcesChapteridentifyareaintheconterminousUnitedStateswastimberland,andtheprojectedamountofnon-FederalforestlandusechangetimberlandareafuturesfollowthesametrendsasforestlandundertheRPAscenario-climatefutures(seethesidebarRPAusefuturestoalargedegree.However,becausetimberlandScenariosforadescriptionoftheRPAscenariosandnamingispartiallydefinedbygrowthpotential,timberlandareacanconventionsusedthroughoutthechapter).Theprojectionsdecreaseduetoproductivitychangesinadditiontochangespresentedinthischapteraccountforthepublicandprivateinlanduse.forestlandbase,butlandusechangesareonlyprojectedfor6-14FutureofAmerica’sForestsandRangelandsRPAScenariosTheRPAAssessmentusesasetofscenariosofcoordinatedFigure6-16.Characterizationofthe2020RPAAssessmentscenariosfutureclimate,population,andsocioeconomicchangetointermsoffuturechangesinatmosphericwarmingandU.S.projectresourceavailabilityandconditionoverthenext50socioeconomicgrowth.Thesecharacteristicsareassociatedwithyears.ThesescenariosprovideaframeworkforobjectivelythefourunderlyingRepresentativeConcentrationPathway(RCP)–evaluatingaplausiblerangeoffutureresourceoutcomes.SharedSocioeconomicPathway(SSP)combinations.The2020RPAAssessmentdrawsfromtheglobalscenariosSource:Langneretal.2020.developedbytheIntergovernmentalPanelonClimateChangetoexaminethe2020to2070timeperiod(IPCC2014).TheRPAscenariospairtwoalternativeclimatefutures(RepresentativeConcentrationPathways,orRCPs)withfouralternativesocioeconomicfutures(SharedSocioeconomicPathways,orSSPs)inthefollowingcombinations:RCP4.5andSSP1(lowerwarming-moderateU.S.growth,LM),RCP8.5andSSP3(highwarming-lowU.S.growth,HL),RCP8.5andSSP2(highwarming-moderateU.S.growth,HM),andRCP8.5andSSP5(highwarming-highU.S.growth,HH)(figure6-16).Thefour2020RPAAssessmentscenariosencompasstheprojectedrangeofclimatechangefromtheRCPsandprojectedquantitativeandqualitativerangeofsocioeconomicchangefromtheSSPs,resultinginfourdistinctfuturesthatvaryacrossamultitudeofcharacteristics(figure6-17),andprovidingaunifyingframeworkthatorganizestheFigure6-17.Characteristicsdifferentiatingthe2020RPAAssessmentscenarios.ThesecharacteristicsareassociatedwiththefourunderlyingRepresentativeConcentrationPathway(RCP)–SharedSocioeconomicPathway(SSP)combinations.2020ResourcesPlanningActAssessment6-15RPAAssessmentnaturalresourcesectoranalysesaroundafinerspatialscales.Althoughthesamemodelswereselectedtoconsistentsetofpossibleworldviews.TheScenariosChapterdevelopclimateprojectionsforbothRCPs,therearedistinctdescribeshowtheseclimatemodelswereselectedandpaired;climateprojectionsforeachmodelassociatedwithRCP4.5moredetailsareprovidedinLangneretal.(2020).andRCP8.5.TheScenariosChapterdescribeshowtheseclimatemodelswereselected.JoyceandCoulson(2020)giveThe2020RPAAssessmentpairsthesefourRPAscenariosamoreextensiveexplanation.withfivedifferentclimatemodelsthatcapturethewiderangeofprojectedfuturetemperatureandprecipitationacrosstheThroughouttheRPAAssessment,individualscenario-climateconterminousUnitedStates.AnensembleclimateprojectionfuturesarereferredtobypairingRPAscenarioswiththataveragesacrossthemultiplemodelprojectionsisnotusedselectedclimateprojections.Forexample,ananalysisrunbecauseoftheimportanceofpreservingindividualmodelunder“HL-wet”assumesafuturewithhighatmosphericvariabilityforresourcemodelingefforts.ThefiveclimatewarmingandlowU.S.populationandeconomicgrowthmodelsselectedbyRPArepresentleastwarm,hot,dry,wet,(HLRPAscenario),aswellasawetterclimatefortheandmiddle-of-the-roadclimatefuturesfortheconterminousconterminousUnitedStates(wetclimateprojection).UnitedStates(table6-1);however,characteristicscanvaryatTable6-1.Fiveclimatemodelprojectionsselectedtoreflecttherangeofthefullsetof20availableclimatemodelsintheyear2070.EachmodelwasrununderRCP4.5andRCP8.5,providingarangeofdifferentU.S.climateprojections.ClimatemodelLeastwarmHotDryWetMiddleInstitutionIPSL-CM5A-MRNorESM1-MMRI-CGCM3HadGEM2-ESCNRM-CM5InstitutPierreSimonNorwegianClimateMeteorologicalMetOfficeHadleyLaplace,FranceNationalCentreCenter,NorwayResearchInstitute,Centre,UnitedofMeteorologicalKingdomResearch,FranceJapanRCP=RepresentativeConcentrationPathway.Source:JoyceandCoulson2020.Timberlandareaisprojectedtodecreasebetween8.4millionamountoftimberlandlossexceedstheoveralllossofforestacres(HL-hot)and15.1millionacres(HH-leastwarm)land.Forexample,thehotclimateprojectionconsistentlybetween2020and2070(table6-2).Timberlandfuturesareleadstomoretimberlandlossthanforestlandloss.ThisstronglydrivenbylandusechoicesunderthedifferentRPAsuggeststhatunderthehotclimateprojection,someless-scenarios.AlthoughtimberlandfuturesaremostsensitiveproductivetimberlandwilltransitiontootherforestlandovertoRPAscenario,thereareclimateprojectionsforwhichthetheprojectionperiod.Table6-2.ProjectednetchangeintimberlandareaandpercentchangeTimberlandareaprojectionsdifferbyRPAregion(figurefrom2020to2070.Theextentoftimberlandin2020was498millionacres.6-18).MosttimberlandlossisexpectedintheSouth,whereChangeandpercentchangearebasedonaveragingprojectionresultsforeachbetween5.7(HL-hot)and10.1(HH-leastwarm)millionRPAscenario-climatefuture.acresareexpectedtobelostprimarilytodevelopedusesby2070.ThePacificCoastRegionisexpectedtoloseScenarioClimateprojectionbetween1.6and2.5millionacresoftimberlandunderHL-LeastHotDryWetMiddlehotandHH-leastwarm,respectively.TheprojectedrangeLMwarmoftimberlandlossintheNorthRegionis0.9(HL-hot)toHL2.2millionacres(HH-wet).TimberlandareaintheRockyHMmillionacres(percent)MountainRegionisthemoststableovertheprojectionHH-13.2(-2.7)-12.3(-2.5)-12.2(-2.5)-12.8(-2.6)-12.9(-2.6)period,losingbetween0.25millionacres(HL-hot)and-11.8(-2.4)-8.4(-1.7)-11.2(-2.2)-11.4(-2.3)-11.5(-2.3)0.4millionacres(HH-dry).Aswithforestarea,economic-12.9(-2.6)-9.4(-1.9)-12.1(-2.4)-12.3(-2.5)-12.5(-2.5)andpopulationchangeistheprimarydriverdifferentiating-15.1(-3)-11.3(-2.3)-14.3(-2.9)-14.6(-2.9)-14.6(-2.9)futuretimberlandarea,withthelargestlossoftimberlandprojectedunderthehigh-growthHHRPAscenario,LM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highfollowedbythemoderate-growthLMandHMscenarios,warming-moderateU.S.growth;HH=highwarming-highU.S.growth.andthenthelow-growthHLRPAscenario(figure6-18).6-16FutureofAmerica’sForestsandRangelandsForestPlantingFigure6-19.Plantedforestareain2020andprojectedto2070fortheconterminousUnitedStatesbyRPAscenario.ProjectedplantedareaisbasedWhileforestplantingisamanagementtoolusedforforestonaveragingdecadalprojectionresultsacrossclimateprojectionswithineachrestorationandtoenhanceorcreatewildlifehabitat,aRPAscenario.largemajorityoftheNation’splantedforestisatimberlandinvestmenttoproduceroundwoodforforestproducts.The80decisiontoplantorreplantafterharvestingthereforedependsontimberpricesandexpectationsofthosepricesovertime.75Becauseprojectionsoffutureplantedforestareadependontimberprices,wereviewtheroundwoodpriceprojectionsMillionsofacres70discussedintheForestProductsChapter,whichdifferbyRPAscenarioandRPAregion.Roundwoodpricesareexpected65tobelowestundertheHLRPAscenario,wherepricesin2070areprojectedtobeonlyslightlyabove2015prices.The60LMandHMscenarioshavesimilarpricetrajectories,wherepricesincreaseatamoderateratefrom2020to2070.The55HHscenariohasthelargestpriceincrease,whereroundwoodpricesareexpectedtoincreaseby1.4timesforsoftwoodand2020203020402050206020702timesforhardwoodfrom2015values.ThedifferentpricepathsforeachRPAscenarioleadtodifferentforestplantingYearandreplantingratesovertime.LMHLHMHHUnderallRPAscenarios,plantedforestareaisprojectedtoincreasebetween4percent(HL)and6percent(LM)LM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highuntil2040(figure6-19).From2040to2070,plantedareawarming-moderateU.S.growth;HH=highwarming-highU.S.growth.Figure6-18.Timberlandareachangeperdecade,startingfrom2020andprojectedoutto2070,byRPAregionandRPAscenario.ProjectedtimberlandareaisbasedonaveragingdecadalprojectionresultsacrossclimateprojectionswithineachRPAscenarioandRPAregion.LMHLHMHHLM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.2020ResourcesPlanningActAssessment6-17isexpectedtodecreaseundertheHLandHMscenariosandtothePacificCoastRegionwheretheplantedforestareaisremainrelativelyconstantundertheLMandHHscenarios.expectedtoincrease.TheHLscenarioleadstoaprojectedlossof1.7millionacresofplantedforestbetween2020and2070.TheHMscenarioTheloblolly/shortleaf,Douglas-fir,andwhite/red/jackpineforestprojectionssuggestthattheareaofforestplantationsin2070typegroupsareimportanttosoftwoodroundwoodsupplyandwillbesimilartothe2020extent(67.7millionacres),whilethereforeworthindividualexamination.OvertheprojectiontheLMandHHprojectionssuggestanincreaseof3.75millionperiod,theproportionoftheDouglas-firgroupthatisplantedacresand3.5millionacresbetween2020and2070,respectively.isprojectedtoincrease,whiletheplantedproportionoftheAsdiscussedintheForestProductsChapter,althoughtheLMwhite/red/jackpinegroupisexpectedtodecreasedespiterisingscenariohasamediumeconomicgrowthviewofthefuture,roundwoodprices.Theplantedproportionoftheloblolly/thereisalsogreaterdemandforbioenergy;thisleadstosimilarshortleafgroupisprojectedtoincreaseundertheHHandLMpricetrajectoriesforLMandHH.TheLMscenario,however,scenariosbutdecreaseundertheHMandHLscenarios.haslesslandusechangepressurethantheHHscenario,whichleadstoslightlymoreinvestmentinplantedforestsunderTimberlandAreabyForestTypeGroupLM.ThehighertimberpricesunderbothLMandHHleadtosustainedplantingovertheprojectionperiodasforestlandusesFutureextentsofforesttypegroupsareimpactedbylandusearemorecompetitiveagainstotherlandusechoices.change,forestmanagement,forestsuccession,andclimate.WepresentprojectionsoffuturetimberlandareabyforesttypeThenationalplantedareaprojectiontrendsareprimarilygrouptobeconsistentwithhistoricdatapresentedinthesectiondrivenbyplantingandreplantingintheSouthRegion,whichHistoricalTrends–TimberlandAreabyForestTypeGroup.contained71percentofplantedforestin2020.PlantedareaIngeneral,themajorFTGsinthewesternRPAregionsaretrendsintheSouththereforemirrorthenationaltrends.Intheprojectedtochangelessinareabetween2020and2070thantheNorthandRockyMountainRegions,plantedforestareaismajorFTGsintheeasternRPAregions,whichinsomecasesexpectedtodecreaseovertheprojectionperiod,asopposedexceed4millionacresofprojectedchange(figure6-20).OftheFigure6-20.Projectednetchangeintimberlandareafrom2020to2070fortheforesttypegroupswiththelargestarealextentin2020byRPAscenario-climatefuture.TenoftheforesttypegroupsprimarilyoccurintheEasternUnitedStatesandsixprimarilyoccurintheWesternUnitedStates.NetchangeisbasedonaveragingprojectionresultsforeachRPAscenario-climatefuturebyforesttypegroup.Netchange(millionacres)RPAScenarioLM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.6-18FutureofAmerica’sForestsandRangelands16majorforesttypegroupsbasedon2020arealextent,onlyforcommerciallyimportantFTGs,whilechangesinclimatetheloblolly/shortleaf,oak/hickory,andwhite/red/jackpinereflectedintheclimateprojectionsresultinrangeshiftsthatgroupsareprojectedtoincreaseinarea.varyacrossFTGs.ManyFTGsareexpectedtoshiftovertimeaspartofTimberlandVolumenormalsuccessionarytrends.However,bothclimaticandsocioeconomicfuturescanalterorinfluencechangesintheThefutureinventoryintermsofvolumeisinfluencedbyshiftsarealextentofeachFTGovertime.Hereweexaminetheinproductivity,landusechoices,managementactionsandsensitivityofprojectedfuturesinFTGextenttothechoiceobjectives,andmarkets.TimberlandgrowingstockvolumeofRPAscenarioversusthechoiceofclimateprojection,isprojectedtoincreaseuntil2050(figure6-22).After2050,accountingfordifferingunderlyingsuccessionarytrends.growingstockvolumesbecomemoresensitivetoRPAIngeneral,thesensitivityofchangesintimberlandareatoscenario,becausetheyareinfluencedmorebychangesRPAscenarioandclimateprojectiondependsontheFTGinlanduseandroundwooddemandthanbyclimate.For(figure6-21),withcommerciallyimportantFTGssuchasexample,in2070,themaximumvolumedifferenceamongloblolly/shortleafandDouglas-firbeingmoresensitivetoclimateprojectionswithinascenarioisapproximately10.6RPAscenario,whileothers,suchaslongleaf/slashpineandbillioncubicfeet,whilethemaximumdifferenceamongmaple/beech/birch,aremoresensitivetoclimateprojection.RPAscenarios(averagedacrossclimateprojections)isSensitivitytoRPAscenarioand/orclimateprojectioncanapproximately41.3billioncubicfeet.Thissuggeststhechoiceleadtoincreasesordecreasesintimberlandarea:whiletheofRPAscenarioisabout3.9timesmoreinfluentialthantheloblolly/shortleafpineandoak/gum/cypressgroupsarebothchoiceofclimateprojectionwhenprojectingtotheendofthehighlysensitivetoRPAscenario,thehigh-economic-growthperiod.UndertheHLandHMRPAscenarios,whichhaveHHscenarioleadstoincreasedtimberlandareaforloblolly/lesslandusechangeandlessharvest,growingstockvolumeshortleafpinebutdecreasedtimberlandareaforoak/gum/isprojectedtoincreasetobetween1,198billioncubicfeetcypress.Similarly,thehotclimateprojectionleadstoless(HM-middle)and1,244billioncubicfeet(HL-leastwarm)intimberlandareaforthemaple/beech/birchgroupbutmore2070.UndertheHHandLMscenarios(morelandusechangetimberlandareaforthelongleaf/slashpinegroup.Ingeneral,andharvest),volumeisexpectedtoincreaseuntilmid-century,economicgrowthreflectedintheRPAscenariospromotesthendecreasetobetween1,136billioncubicfeet(HH-dry)andincreases(oratleastmitigatesdecreases)totimberlandarea1,161billioncubicfeet(LM-wet).Figure6-21.SensitivityoftimberlandareaprojectionstoclimateprojectionTherearedistinctregionalpatternswithrespecttogrowingandRPAscenarioforselectedforesttypegroups.Sensitivityiscalculatedstockvolumefutures(figure6-23).IntheNorth,bothhardwoodasameasureofseparabilitybetweenprojectionsamongdifferentclimateandsoftwoodgrowingstockinventoriesareprojectedtoprojectionsandRPAscenarios.increaseacrossRPAscenariosthroughouttheprojectionperiod.HardwoodinventoryismoresensitivetodemandbecausetheNorthisprojectedtoremainanimportanthardwoodroundwoodproducer.Lowerroundwood-demandRPAscenarios(HL,HM)leadtofutureswithmorehardwoodgrowingstockvolume.GrowingstockvolumeintheSouthismoresensitivetoRPAscenariothantheotherregionsofthecountry.ProjectedsoftwoodgrowingstockvolumeincreasesacrossRPAscenariosuntil2050andthendeclines,withthelargestdeclinesassociatedwiththeLMandHHscenarios.ProjectedhardwoodgrowingstockvolumeincreasesacrossRPAscenariosuntil2050andcontinuestoincreaseunderHLandHM.TheRockyMountainRegionisasoftwood-dominatedregion,wherefuturegrowingstocksoftwoodvolumeisexpectedtodecreaseacrossRPAscenarioswhilehardwoodvolumeisexpectedtoremainrelativelystable.TheRockyMountainRegionisratherinsensitivetoRPAscenario,inlargepartbecauseroundwooddemandintheregionissignificantlysmallerthanintheotherregions.ThePacificCoastisalsoasoftwood-dominatedregion,andsoftwoodgrowingstockvolumeisprojectedtoincrease2020ResourcesPlanningActAssessment6-19Figure6-22.Growingstockvolumeontimberlandin2020andprojectedto2070fortheconterminousUnitedStatesbyRPAscenario-climatefuture.ProjectedgrowingstockvolumeontimberlandisbasedonaveragingdecadalprojectionresultsbyRPAscenario-climatefuture.LMHL1,2501,2001,1501,1001,050Billionsofcubicfeet1,000950HMHH1,2501,2001,1501,1001,0501,000LM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=high950warming-highU.S.growth.202020302040205020602070202020302040205020602070YearFigure6-23.Historicalandprojectedgrowingstockvolumeforhardwood/softwoodbyRPAscenarioandRPAregion.ProjectedgrowingstockvolumeisbasedonaveragingdecadalprojectionresultsacrossclimateprojectionswithineachRPAscenario,RPAregion,andspeciesgroup.NorthSouth200100Billionsofcubicfeet0PacificCoastRockyMountains2001000LM=lowerwarming-moderateU.S.growth;HL=highwarming-low1975U.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.2000202520501975200020252050Year6-20FutureofAmerica’sForestsandRangelandsthrough2050acrossRPAscenarios,whilehardwoodgrowingFigure6-24.HistoricalandprojectedannualremovalvolumeontimberlandstockvolumeisprojectedtodeclineslightlythroughouttheacrosstheconterminousUnitedStates,byRPAscenario.Projectedannualprojectionperiod.SimilartotheSouth,post-2050softwoodremovalvolumeisbasedonaveragingdecadalprojectionresultsacrossclimategrowingstockfuturesdependonroundwooddemand,whereprojectionswithineachRPAscenario.softwoodgrowingstockvolumeareprojectedtodecreasepost-2050undertheLMandHHscenarios.RemovalsHistoricalLMHLHMHHProjectionsofgrowingstockremovalsontimberlandareLM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highstronglydrivenbytheunderlyingmarketdemandforroundwoodwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.associatedwiththeRPAscenarios,wherethehigh-growthHHRPAscenarioin2070suggestssubstantiallymoregrowingstockremovals(19billioncubicfeetperyear)ontimberlandthanthelow-growthHLscenario(13.8billioncubicfeetperyear;figure6-24).BoththeHHandLMscenariossuggestarecoverytopre-recession(2006to2007)levelsby2050buttheHLandHMscenariosdonotrecovertopre-recessionlevels.WhileboththeLMandHMscenariosassumemoderategrowth,theLMscenariosuggestsacommitmenttowardsustainabilityanduseofbioenergy,whichincreasesforestremovalsovertheHMscenario.Hardwoodandsoftwoodremovalsaregenerallyprojectedtorecoverfromthelowsthatoccurredinthe2000sineachregion,buttheNorthandSouthRegionsareexpectedtoshowsubstantialincreasesinallremovalsby2070relativeto2020removals(figure6-25).TheseincreasesroughlymirrorFigure6-25.Historicalandprojectedremovalvolumeontimberlandforhardwood/softwoodbyRPAscenarioandRPAregion.ProjectedremovalvolumeisbasedonaveragingdecadalprojectionresultsacrossclimateprojectionswithineachRPAscenario,RPAregion,andspeciesgroup.NorthSouth864Billionsofcubicfeetperyear20PacificCoastRockyMountains8642LM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=high0warming-highU.S.growth.19752000202520501975200020252050Year2020ResourcesPlanningActAssessment6-21projectedwoodprices(seetheForestProductsChapter).successioncanleadtoasignificantdeparturefromlinearAswithtrendsacrosstheconterminousUnitedStates,RPAaging.Underlinearaging,allforestlandwouldage50yearsscenarioimpactstherateofthisrecovery,andinsomeoverthe50-yearprojectionperiod,butforestmanagement,cases,whetherremovalsareexpectedtoreturntopre-2000sdisturbance,andsuccessiongenerallyreducetheagelevels(e.g.,softwoodsintheRockyMountainandPacificofforests.Inaddition,theRPAscenarioshavedifferentCoastRegionsandhardwoodsintheSouthRegion).Intheassumptionswithrespecttoforestinvestment,whichNorth,projectionsofhardwoodremovalsvaryfrom1.88leadstoslightlydifferentfutureswithrespecttoforestagebillioncubicfeetperyearby2070undertheHLscenariodistribution.Forestagedistributionisimportantbecauseitis(5.0percentabove2020levels)to2.54billioncubicfeetcorrelatedwithforeststructuralcomponents.peryearundertheHHscenario(41.9percentabove2020levels),asdrivenbytheeconomicgrowthassumptionsAcrossRPAscenarios,theaverageageofforestincreasesinherentintheseRPAscenariosandtoalesserextentbyby14yearsintheEastand10yearsintheWestoverthelandusechoices.Similarly,softwoodremovalsintheprojectionperiod.IntheEast,allprojectionssuggestanSouthareprojectedtovaryfrom5.89billioncubicfeetincreaseinproportionofforest80+yearsoldandadecreaseperyearin2070undertheHLscenario(4.1percentmoreintheproportionofforestlessthan80yearsoldby2070.than2020levels)to8.08billioncubicfeetperyearunderHowever,theamountofforestmanagementdrivenbytimbertheHHscenario(42.8percentmorethan2020levels).InpricesassociatedwiththeLMandHHscenariosleadstolessthePacificCoastandRockyMountainRegions,softwood80+yearoldforestby2070thantheotherscenarios(figureremovalsmayreturnto2006levels,butnoprojection6-26),aswellasyoungforests(0to9yearsold)havingaresultsinpre-2000sremovallevels.similararealextenttotheforestsof2020.IntheWest,theproportionofforest100+yearsoldisprojectedtoincrease,ForestAgingandStructurewithrelativelylargeincreasesinthe150+yearageclass.Theprojectionsalsosuggestanincreasein30-to40-year-oldForestswillageovertheprojectionperiod;however,theforestasaresultofforestmanagementanddisturbance.Likeimpactsofforestmanagement,disturbance,andforesttheEast,projectionsforthe0-to9-yearageclassareslightlyhigherundertheLMandHHscenarios.Figure6-26.Forestagedistributionin2020andprojectedforestagedistributionin2070byRPAscenariofortheEasternandWesternconterminousUnitedStates.Theprojectedagedistributionisbasedonaveragingthe2070projectionresultsacrossclimateprojectionswithineachRPAscenariofortheEasternandWesternUnitedStates.20202070–LM2070–HL2070–HM2070–HHNote:150-yearageclassrepresentsageclasses150-yearsandolder.LM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.6-22FutureofAmerica’sForestsandRangelandsThecombinationofforestaging,forestdisturbances,forestincommerciallyimportantforesttypesthatarecommonlymanagement,andlandusechangeaffectsforeststructure.plantedsuchasloblollypine,Douglas-fir,andponderosapine.OnewaytoinvestigateshiftsinforeststructureistoexamineForexample,projectionssuggestanincreaseinthenumberhowthenumberoftreesbydiameterclassandtreevolumebyoftreesacrossdiameterclassesfortheloblolly/shortleafpinediameterclasschangeovertime.Asforestsage,thenumbergroup,withthelargestincreasesseenforthe1-and3-inchofsmallertreestypicallydecreasewhilethenumberoflargerdiameterclassesunderthehighroundwooddemandRPAtreesincrease(DavisandJohnson1987).Simultaneously,scenarios(LMandHH).TheDouglas-firandponderosavolumeinthelargertreesizeclassesincreases.Projectionsinpinegroupshadsimilarprojectedtrendsforsmall-diametertheEastsuggestadecreaseinthenumberofsaplings(smalltrees.Otherforesttypesthatpredominantlyrelyonnaturaltreeslessthan5inchesindiameter)andthenumberoftreesinregenerationshowedadifferentpattern.Theoak/hickory,the5-inchdiameterclass(figure6-27).IntheWest,thistrendoak/gum/cypress,andCaliforniamixedconifergroupsarecontinuesthroughthe13-inchdiameterclass.Increasesintheprojectedtodecreasewithrespecttosmall-diametertrees.numberoftrees(occurringforthe7+inchclassesintheEastOakregenerationhasbeenanareaofactiveresearchforandthe15+inchclassesintheWest)differedslightlybyRPAdecadesduetothelackofbothregenerationandadvancedscenario,wherelargerincreasesweregenerallyprojectedforregeneration(Iversonetal.2017),andthefactthatCalifornialowerroundwooddemandscenarios(HLandHM).mixed-coniferregenerationisaffectedbyfiresuppression,harvesting,andotherforestmanagementactivities(WelchAdecreaseinthenumberofsmallerdiametertreescanoccuretal.2016).Projectionsfortheseforesttypegroupssuggestforseveralreasons,includinglessafforestation(grosslandusecontinueddecreasesinthenumberofsaplingsinthe1-andgains),lessforestmanagement,andlessregeneration.Based3-inchdiameterclassesacrossRPAscenarios.onDomkeetal.(2021),about2.5millionacresofnonforestlandtransitionedtoaforestlandusein2019,whereaslandWhiletheprojectedshiftsinthenumberoftreesbydiameterusechangeprojections(seetheLandResourcesChapter)classmayappearsubtle,theseshiftshavealargeeffectonsuggestthatonaveragefrom2020to2070about0.5millionthevolumedistributionbydiameterclass,particularlyforacresperyearoflandmaybeconvertedtoaforestuse.Thediameterclasseslargerthan5inchesintheEastandlargerprojecteddecreaseinafforestationdoesinfluencethenumberthan13inchesintheWest(figure6-28).Theincreaseinofsmall-diametertrees.Usingforestremovalsasaproxytothenumberoftreesinlargerdiameterclassesleadstoanindicateforestmanagement,forestmanagementisprojectedtooutwardshiftinthevolumebydiameterclassdistribution.remainrelativelystable(HL)orincrease(LM,HM,HH)fromIntheEast,largeincreasesinvolumeareprojectedin13+-2020levels;however,forestmanagementismoreintensiveinchdiameterclassesascomparedtotheWest,wherelargeFigure6-27.Foresttreedistributionbydiameterclassin2020andprojectedforesttreedistributionin2070byRPAscenariofortheEasternandWesternconterminousUnitedStates.Theprojectedtreedistributionbydiameterclassisbasedonaveragingthe2070projectionresultsacrossclimateprojectionswithineachRPAscenariofortheEasternandWesternUnitedStates.20202070–LM2070–HL2070–HM2070–HHLM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.2020ResourcesPlanningActAssessment6-23Figure6-28.Forestvolumedistributionbydiameterclassin2020andprojectedforestvolumedistributionin2070byRPAscenariofortheEasternandWesternconterminousUnitedStates.Theprojectedvolumedistributionbydiameterclassisbasedonaveragingthe2070projectionresultsacrossclimateprojectionswithineachRPAscenariofortheEasternandWesternUnitedStates.20202070–LM2070–HL2070–HM2070–HHLM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.volumeincreasesareprojectedforthe17+-inchdiameterrelevanttoforestCaccounting:forestremainingforest,landsclasses.Thehigherroundwood-demandRPAscenarios(LMconvertedtoforest,andforestconvertedtootherland(seeandHH)areprojectedtohavelessvolumeinthelarger-thesidebarDefinitions).Theforestremainingforestlanddiameterclassesbecauseofincreasedharvestrates.baseisofparticularinterest,ascarbondynamicsonthatlandrepresentinteractionwiththeatmosphere.ThelandsForestSectorCarbonconvertedtoforestandforestconvertedtootherlandusesrepresentlandusetransfersofC,aswellassequestrationTheforestsoftheUnitedStatesprovideasuiteofecosystemandemissions.UndertheIPCCguidelines,standardforestCservices,includingthestorageandsequestrationofpoolsusedforreportingincludeCinabovegroundbiomass,carbon(C).ForestsectorCincludesCstoredinforestedbelowgroundbiomass,deadwood,litter,andsoil.ecosystems,Cstoredinnewforestareas,andCstoredinlong-livedforestproducts.Withinforests,CflowsinfromTherearetwootherpoolsofCrelevanttoforestry:harvestedtheatmospherethroughphotosynthesisandisstoredinlivingwoodproducts(HWP)andHWPstoredinsolidwastetrees,seedlings,andsaplings.Whileforestsaresequesteringdisposalsites(SWDS).HarvestedtreesusedforproductsareC,theyarealsoemittingCthroughrespiration,aswellasnotacompleteemissionofCtotheatmosphere,eventhoughcyclingCthroughnon-livepoolssuchasdeadwood,thetheyareremovedfromforests,becauseaportionofthelitterlayer,andsoils.TheamountofCstoredinforestsandharvestedroundwoodisstoredinlong-livedwoodproducts.theannualrateatwhichtheysequestercarbonarefunctionsForexample,aportionofthesoftwoodharvestintheUnitedofbiologicalprocesses(e.g.,forestgrowth,aging),edaphicStatesisusedtoproducedimensionallumber(e.g.,2x4s):factors(e.g.,sitequality),human-mediatedandnaturalthesawtimberportionofthetreeisusedfordimensionaldisturbances(e.g.,harvesting,wildfire),landusechange(e.g.,lumber,whileotherportionsofthetreeareusedforotherlandsconvertedtoforest,forestconvertedtootherlands),andproducts(e.g.,thetopmaybechippedforpulpandresiduesinteractionsamongthesedrivers.ForestsintheUnitedStatesfromthesawingprocessmaybeusedtogenerateelectricity),havehistoricallyoffsetaportionofCemissionsfromandtheunusedportionofthetreeremainsonsiteasloggingothersectors.residue.Walletal.(2018)suggestthatabout13percentofatree’svolumeisleftasloggingresiduetodecomposeandemitTheUnitedStates,asasignatoryoftheUnitedNationsCintotheatmosphere.TheCinlong-livedwoodproducts,FrameworkConventiononClimateChange,followshowever,remainsstoredwhiletheproductsareinuse.AttheIntergovernmentalPanelonClimateChange(IPCC)endofuse,theproductsandtheCtheycontainarediscardedguidelinesforCaccounting(IPCC2006).WithrespecttoandmovedtoSWDS(Skog2008).forests,therearethreeprimarylandusecategoriesthatare6-24FutureofAmerica’sForestsandRangelandsCarbonremainsanactivetopicinbothscienceandpolicyhere,theUSDAForestServicedoesprovidecontemporaryasregional,national,andglobalemissionreductiontargetsestimatesforAlaska,andforadditionalpoolssuchasorganicareidentified.ForestsequestrationofCintheUnitedStatessoilC,Cemissionfromdrainedorganicsoils,andinformationiscriticalbecauseitoffsetsapproximately11percentofonnon-CO2emissionsaspartofthenationalgreenhousegasemissionsfromothersectors(Domkeetal.2021).Severalinventoryreport(USEPA2021)andinanalysisbyDomkeetpoliciesareeitherinplaceorbeingconsideredtoincreaseal.(2021).Wepresentourfindingsinmetricunitstofacilitatethesequestrationrateofforeststhroughnaturalclimatecomparisonstotheliteratureandinternationalcomparisons.solutions;thesepoliciesenableforeststooffsetalargershareofCemissionsasemissionsarereducedinothersectors.HistoricalForestSectorCarbonTrendsGriscometal.(2017)examinedtheimpactsofpotentialnaturalclimatesolutions—includingreforestation,avoided❖Forestcarbonstocksconsistentlyincreasedfromforestconversion,naturalforestmanagement,improvedplantations,avoidedwoodfuel,andfiremanagement—to1990to2019.increaseforestCsequestration,findingthatreforestationandavoidedforestconversionshowedthegreatestpotential.❖GrowthintheabovegroundbiomasscarbonOthershaveexaminedmorespecificforestmanagementactivitiesandoptionstoincreaseforestCsequestration;forpoolaccountedformorethan67percentoftheexample,Fargoineetal.(2018)foundthatextendingrotationincreaseincarbonstocks.lengthswouldincreaseforestCsequestration.WhilenaturalclimatesolutionsofferapproachestoincreasetheforestC❖Carbonstorageinharvestedwoodproductssinkstrength,futureclimateandsocioeconomicshiftscreateuncertaintyinthelong-termeffectivenessofthepotentialandsolidwastedisposalsitesaccountedfor14approaches(Zhuetal.2018,Tianetal.2018).Thefirstsectionpercentofforestsectorstockchangein2019.presentshistoricforestCtrendsintheUnitedStates,whiletheForestSectorCarbonProjectionssectiondescribestheForestEcosystemCarbonrangeofCoutcomesacrossRPAscenario-climatefuturesandexaminestheirrelativesensitivitytothesefutureswhileTotalforestremainingforestCintheconterminousUnitedaccountingfortheecologicalprocessesthatgoverntheforestsStatesincreasedfrom40.6billionmetrictonsC(BMTC)inoftheUnitedStates.1990to45.5BMTCin2020(table6-3),anincreaseof12.6percentoverthatperiod.ThisincreasewasprimarilydrivenOurpresentationofhistoricaltrendsandprojectionsisbynetafforestationandforestgrowth,exceedingtheeffectsbasedontheconterminousUnitedStates.Werestrictourofdisturbances(includingforestharvesting).TheannualpresentationtoonlythoseCpoolsdescribedaboveandCstockchangerangedfrom173millionmetrictonsCperonlyconsidersoilCinmineralsoils.Althoughnotincludedyear(MMTCyr-1)in1990to155MMTCyr-1in2019.Theaveragehectareofforestremainingforestlandsequestered0.6megagramsperhectareperyearin2019(Mgha-1yr-1)(Domkeetal.2021).AnnualCstockchangewasbetween0.3percentand0.4percentoftheCstockamount,whichsuggestsTable6-3.Carbonstocks(BMT)andstockchanges(MMTyr-1)from1990to2020intheconterminousUnitedStatesforforestecosystempoolsandharvestedwoodpools.Stockchangesareprovidedinparentheses.YearCarbonpool1990199520002010201520192020Forestecosystemtotal40.61(173)41.46(168)BMTC(MMTCyr-1)45.35(155)45.51(--)Abovegroundbiomass11.08(120)11.67(116)14.33(104)14.43(--)Belowgroundbiomass2.23(24)2.35(24)42.30(164)43.90(161)44.70(166)2.89(21)2.91(--)Deadwood1.78(26)1.91(27)2.56(27)2.59(--)Litter2.42(2)2.43(2)12.25(112)13.35(109)13.89(112)2.47(1)2.47(--)Soil(mineral)23.09(0)23.09(0)23.10(2)23.11(--)Landconvertedtoforest2.47(23)2.69(22)2.80(22)Harvestedwoodtotal--(27)--(27.1)--(27.3)--HWP1.90(34)2.06(31)2.05(27)2.32(27)2.45(28)2.67(30)--SWDS1.25(15)1.33(14)1.52(11)--Total0.65(19)0.74(17)2.44(2)2.46(1)2.46(1)1.15(19)--42.51(234)43.53(226)48.02(213)--23.09(0)23.09(1)23.10(2)--(27.1)--(27.2)--(27.2)2.22(26)2.46(19)2.57(24)1.40(9)1.47(2)1.49(7)0.82(17)0.99(17)1.08(18)44.52(217)46.37(206)47.27(216)BMT=billionmetrictons;C=carbon;HWP=harvestedwoodproducts;MMT=millionmetrictons;SWDS=solidwastedisposalsite;yr=year.2020ResourcesPlanningActAssessment6-25thatrelativelysmallchangesovertheentireforestremainingabovegroundbiomass,wherethedensityincreasedfrom44.2forestlandbasedrivethestockchangerates.GrowthintheMgCha-1in1990to57.6MgCha-1in2020.abovegroundbiomasspoolaccountedfor67percentofthetotalCstockchangein1990and70percentin2019.OtherLandConvertedtoForestCarbonCarbonisdistributedunevenlyacrosspools.In2020,Changesintheforestlandbasehavealsoinfluencedtheforexample,over80percentofCwasstoredineitheramountofcarbonstoredandsequesteredbyforests(Woodallabovegroundbiomass(31.7percent)orsoilpools(50.8etal.2015).Forestsconvertedtootherlandusesandotherpercent)(figure6-29),withbelowgroundbiomass,deadlandsconvertedtoforestsbothconstitutelandusetransfers.wood,andlittercombinedmakinguptheremaining17.5ThetotalCstockontheforestlandbaseinanygivenyearpercent.TheshareofCthateachpoolcontributestotheistheCstockinforestremainingforestplustheCstocktotalhaschangedovertime.Forexample,theabovegroundofotherlandsconvertedtoforest.Since1990,landusebiomasspoolaccountedfor27.3percentofthetotalCfortransfersofChavebeenrelativelystable,wheretheCforestsremainingforestsin1990,whileitaccountedfor31.7transferredfromforesttootherlandusesrangedfrom32percentin2020.Thebelowgroundbiomass,deadwood,andMMTCyr-1to34MMTCyr-1andtheCgainedbytheforestlitterpoolsalsoshowedanincreaseintheirsharesofthetotallandbasefromotherlandusesduetoafforestationwasaboutbetween1990and2020.TheshareoftotalCinthesoilpool27MMTCyr-1(table6-3;Domkeetal.2021).decreasedfrom56.9percentin1990to50.8percentin2020.TheshiftsinpoolcontributionstototalforestecosystemCHarvestedWoodCarbonandTotalCarbonwerepartiallyattributabletochangesinlanduse,buttheywereevenmorestronglydrivenbybiologicalforestgrowth.ChangesinCstorageinHWPandSWDSaccountedforByexaminingstockdensities—thesizeofaCpoolperapproximately16percentofthetotalcarbonstockchangehectareofforest(MgCha-1)—wecontrolforchangesinthefrom1990to2019.CarbonstocksinHWPandSWDShaveamountofforestlanduseandcanexaminechangesduetocontinuedtoincreasesince1990despiteepisodicshiftsinforestgrowth.WhilesoilisthelargestCpool,itwasalsothedemandforroundwoodfromtheUnitedStates(tablethemoststableintermsofdensity,changingonlyslightly6-3):thecombinedHWPandSWDSCstockgrewfrom1.9from92.1MgCha-1to92.2MgCha-1overtheperiod1990BMTCin1990to2.7BMTCin2019.Evenwiththeshiftto2020.ThedensityofCinabovegroundandbelowgroundawayfromnewsprintsince1990,theHWPandSWDSpoolsbiomasspoolsbothincreasedbyabout29percent;however,continuetogrow,albeitatconsiderablymorevariableratesthemagnitudeofthechangewassignificantlylargerforthanthosefortheforestecosystempools.ThetotalstockchangeinforestremainingforestpoolsandharvestedwoodFigure6-29.Theshareoftotalforestecosystemcarbonforeachpoolin2020.poolsrangedfrom206.7MMTCyr-1in1990to184.6MMTCyr-1in2019(table6-3).WhenincludingtheCtransferredfromland-usechange,theforestsectorsequestered212.9MMTCyr-1in2019.6-26FutureofAmerica’sForestsandRangelandsForestSectorCarbonProjectionsWithoutactivemanagement,significantdisturbance,andlandusechange,forestsapproachasteadystateintermsofCstock❖Abovegroundbiomasscarbondensityischangeovertime.Butmanagementanddisturbancedooccur,alongwithchangesinlandusedecisions,whichaffectforestCprojectedtoincreaseby17to25percentfromstocksandstockchange.ForestCfuturesaredrivenbyasuite2020to2070,whileannualcarbonsequestrationoffactorsincludingclimate,landusechange,anddisturbance,isprojectedtodecrease,indicatingcarboninadditiontolimitingfactorsthatcanimpactforestgrowthsaturationofU.S.forests.wheninshortsupply(e.g.,light,nutrients,andwater).AsdescribedintheProjectedFuturesofForestandTimberland❖ForestecosystemcarbonfuturesarestronglyAreasectionofthischapter,forestareaisexpectedtodecreasebetween2020and2070.Atthesametime,disturbancessuchdrivenbyforestgrowthdynamics,roundwoodasfireareexpectedtoincrease(seetheDisturbanceChapter),demand,andtoalesserextentlandusechange.andharvestforwoodproductsisexpectedtoeitherberelativelyTheamountofcarbonsequesteredbyforestsisstable(HLscenario)orincrease(LM,HM,andHHscenarios;projectedtodeclinebetween2020and2070underseetheForestProductsChapter).Theseprojectedchangeswillallscenarios,withtheforestecosystemprojectedaffectforestCfutures.tobeanetsourceofcarbonin2070underthehighroundwooddemandRPAscenario(HH).ForestEcosystemCarbonStocksandChanges❖ForestsintheRockyMountainRegionareForestCarbonLandBaseexpectedtobethemostsensitivetofutureclimatesandwillremainanetcarbonsourceTheamountofforestthathasbeeninacontinuousforestthrough2070.useovertime(“forestremainingforest”–seethesidebarDefinitions)isacriticalfactorinoverallCsequestration❖ConversionofforesttootherusesresultsinbecausethetotalamountofCforestsremovefromtheatmosphereisdependentonthesizeofthelandbasethathasbetween194MMTand517MMTofsoilorganicpersistedinaforestuse,inadditiontoforestconditions.Incarbonbeingtransferredtootherlanduses2020,forestremainingforestlandbaseacrosstheconterminousovertheprojectionperiod.ThereisuncertaintyUnitedStateswas619millionacres.Aswithforestlandregardingtheportionofsoilorganiccarbonthatandtimberland,thearealextentofforestremainingforestisisemittedtotheatmosphereinresponsetoforestexpectedtodeclineovertheprojectionperiod.Thepatternandlandconversion.timingoflossandgeneralresponsetoRPAscenario-climatefuturesisconsistentwithtimberlandprojections(discussedin❖ProjectionssuggestthatcarbonstockchangethesectionFutureProjections–ForestLandandTimberland).Overtheprojectionperiod,theamountofforestremaininginharvestedwoodproductsandsolidwasteforestisexpectedtodecreaseby7.9millionacres(HL-hot)todisposalsiteswillrepresentanincreasingshare15.2millionacres(HH-leastwarm)(table6-4).oftheforestsector’scarbonstockchangeandeventuallycouldbelargerthanforestecosystemstockchangeTable6-4.Projectednetchangeandpercentchangeinforestremainingforestareafrom2020to2070fortheconterminousUnitedStates.ChangeandpercentchangearebasedonaveragingprojectionresultsforeachRPAscenario-climatefuture.RPAscenarioClimatemodel2020forestremainingLMHLHMHHforestLeastwarm-13.2(-2.1)millionacres(percent)-15.2(-2.5)Hotmillionacres-12.1(-2.0)-11.1(-1.8)Dry619-12.2(-2.0)-11.5(-1.9)-12.7(-2)-14.5(-2.3)Wet619-12.7(-2.1)-14.7(-2.4)Middle619-12.8(-2.1)-7.9(-1.3)-8.9(-1.4)-14.7(-2.4)619619-11.0(-1.8)-12.0(-1.9)-11.1(-1.8)-12.1(-2)-11.3(-1.8)-12.4(-2)LM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.2020ResourcesPlanningActAssessment6-27ForestEcosystemCarbonPoolsthattheforestecosystemCsinkwillsaturateandarealsoconsistentwiththeresultsofZhuetal.(2018).TheabovegroundbiomassCpoolistheprimarydriverofoverallCsequestration(Panetal.2011).OurresultssuggestSoilorganicCisthelargestforestremainingforestpool.Thethatthispoolwillincreaseatadecreasingratefrom2020totalCcontentofthepoolisrelatedtothetotalforestremainingto2070.Whilelanduseconversionandfuturedisturbanceforestarea;however,increasedtemperatureandharvestcanplayaroleinreducingfuturesequestrationrates,forestagingalsoinfluencethepool(Kirschbaum2000,Mayeretal.2020)andsenescencearealsodriversofthistrend.AbovegroundthroughincreaseddecayratesandreductionsintheorganicsoilbiomassCisprojectedtoincreaseacrossRPAscenario-horizons(JamesandHarrison2016).Ourresultssuggestthatclimatefuturestobetween16.4BMTC(HH-dry)and17.6soilCwillremainthelargestpoolthroughouttheprojectionBMTC(HL-warm)by2070(figure6-30).Therangeofperiod,butwedoprojectanetdecreaseinsoilorganicCoverabovegroundbiomassCfuturesaremorestronglydrivenbytime.Specifically,projectionssuggestthatsoilorganicCwillRPAscenariothanbyclimateprojection.Thecombinationofremainrelativelystablethrough2030,andthendecreasethroughincreasedlandusepressureandroundwooddemandunderthe2070by0.8percent(HL-hot)to2.2percent(HH-middle).WhileLMandHHRPAscenariosleadstolessabovegroundbiomassthesedecreasesaresmallonapercentagebasis,theyequatetoCstocksin2070thanundertheHLorHMscenarios.atransferofbetween194MMTand517MMTofsoilorganicCovertheprojectionperiod.TheamountofsoilorganiccarbonTheprojecteddensityofabovegroundbiomassCin2070isthatisemittedbacktotheatmosphereduringlandusechangeisbetween66.8MgCha-1(HH-dry)and71.7MgCha-1(HL-uncertainanddependsonthespecificlanduseforestisconvertedwarm).Theseprojecteddensityvaluesarea17-to25-percentto.Conversionofforesttootherusesisthemaindriveroflossinincreasefrom2020anda51-to62-percentincreasefromsoilorganicC,assoilorganicCdensityremainsrelativelystable1990.Inotherwords,theaveragehectareofforestin2070overtheprojectionperiod(92MgCha-1to93MgCha-1).isprojectedtohave51to62percentmoreCstoredinabovegroundbiomassthantheaverageforesthectarehadCinbelowgroundbiomass,deadwood,andlitteraccountsin1990.ThesefindingsareconsistentwiththehypothesisforarelativelysmallcomponentofforestecosystemC.Figure6-30.HistoricandprojectedforestremainingforestabovegroundbiomasscarbonstocksforeachRPAscenario-climatefuture.ProjectedabovegroundbiomassisbasedonaveragingdecadalprojectionresultsbyRPAscenario-climatefuture.LM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.6-28FutureofAmerica’sForestsandRangelandsForestCarbonTrajectoriesForestremainingforestCstocksincreasedatarelativelyStateDepartmentandExecutiveOfficeofthePresidentconsistentratefrom1990to2020,buttherearemany2021).Underexponentialgrowth,CstocksincreaseatpotentialfutureCstocktrajectories.ThreemainalternativeanincreasingrateandresourcesarenotlimitedovertheU.S.trajectoriesaresuggestedintheliteraturewithrespecttimehorizon.AlineartrendimpliesthatresourcesaretoforestCfutures,providingcontextforRPAprojections:sufficienttomaintainsequestrationoverthetimehorizon,forestecosystemCcouldincreaseatanincreasingrateafteraccountingfordisturbanceandlandusechange.(exponentialgrowth),increaseataconstantrate(linearWhenCstocksincreaseatadecreasingrate,anasymptotegrowth),orincreaseatadecreasingrate(logisticgrowth;isimpliedandthecarryingcapacityofthesystemisfigure6-31).Thesethreealternativescovertherangereachedoverthetimehorizon(growthapproacheszero).ofpotentialforestCfuturesusedinaU.S.governmentExaminingourresultsinthecontextofthesethreeanalysisidentifyinglong-termstrategiesandpathwaysalternativetrajectoriescanprovideinsightsaboutthetonet-zerogreenhousegasemissionsby2050(U.S.processesthatleadtoforestCstockchangeinthefuture.Figure6-31.Alternativefuturecarbonstock(left)andstockchange(right)trajectories.C=carbon.WhilethebelowgroundpoolissmallerthantheabovegroundTotalForestEcosystemCarbonpool,projectionsofbelowgroundbiomassCfollowasimilartrajectorytoabovegroundbiomassCintermsofthepercentageTotalCstocksonforestremainingforestareprojectedtochange.Cinbelowgroundbiomassisexpectedtoincreasefromincreasefrom45.5BMTCin2020tobetween47.6BMT2.9BMTCin2020to3.2(HH-dry)to3.5(HL-leastwarm)C(HH-middle)and49.8BMTC(HL-leastwarm)in2070BMTCin2070.LitterCisprojectedtoincreaseuntil2050,and(figure6-32a).Cstockchangein2030isprojectedtobethendecreasethrough2070withlargerdecreasesassociatedwithrelativelyconsistentwith2019stockchangeestimatesandthehotclimateprojection.DeadwoodCisexpectedtoincreasethenisprojectedtodecreaseacrossRPAscenario-climateslightlyovertheprojectionperiod,withthelargestincreasesfuturesfrom2030to2040(figure6-32b).By2070,whetherundertheHMandHLscenarios,suggestingthatRPAscenariostheforestremainingforestlandbasecontinuestobeanetwithlessforestremovalsleadtoincreasedCindeadwood.CsinkdependsontheRPAscenario.TheforestremainingFurther,deadwoodCisfuelforwildfiresandourprojectionsforestlandbaseisprojectedtoremainanetCsinkin2070suggestasloweraccumulationofdeadwoodCwiththeundertheHMandHLRPAscenarios,sequesteringbetweenprojectedincreaseinwildfires(seetheDisturbanceChapter).22and45MMTCyr-1,respectively.The2070forestremainingforestCstockchangeisprojectedtorangefrom6MMTCyr-1to-6MMTCyr-1undertheLMscenario,whileforestremainingforestisprojectedtobeanetsource2020ResourcesPlanningActAssessment6-29Figure6-32.Historicandprojectedforestremainingforest(a)totalforestecosystemcarbonstocksand(b)stockchangesforeachRPAscenario-climatefuture.ProjectedforestecosystemcarbonstockandstockchangeisbasedonaveragingdecadalprojectionresultsbyRPAscenario-climatefuture.(a)TotalForestEcosystemCarbonStocks(b)StockChangesTotalforestecosystemcarbonstocks(billionmetrictons)Totalforestecosystemcarbonstockchange(millionmetrictonsperyear)LM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.Figure6-33.Forestecosystemtotalcarbonstockchangein2019(historic)ofCin2070undertheHHscenario(-7to-26MMTCyr-1).anddecadalprojectionsfor2030to2070byRPAscenario.DecadalprojectedHowever,thereisconsiderablemodelinguncertaintyinvaluesaretheaverageofprojectionresultsbyRPAscenario.ModelingprojectedforestecosystemCstockchanges(figure6-33).uncertaintyisdenotedbythe99percentprojectionintervalsfor2030to2070BasedonprojectionsfromtheForestDynamicsModel,C(blacklines).stockchangecouldbenegative(netCsource)undertheLMandHHscenariosby2050.Themodelinguncertaintyincreaseswiththelengthoftheprojectionperiod,leadingtosignificantuncertaintyby2070,wheretheuncertaintyenvelopeacrossRPAscenariosrangesfromlessthan-100MMTCyr-1(substantialCsource)togreaterthan100MMTCyr-1(substantialCsink).YearRegionalTrendsinTotalForestEcosystemCarbonHistoricLMHLHMHHTrendsinforestecosystemCstocksandstockchangesLM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highdifferbyRPAregion.ThemajorityofCstockswerestoredwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.intheEasternUnitedStatesin2019andtheseregionsweretheprimaryforcebehindsignificantCaccumulationsince1990.Forestgrowth,investmentsinforestmanagement,andafforestationledtoincreasingCstocksataconsistentrate.Incontrast,theforestecosystemsofthewesternRPAregionstypicallyhadslowergrowthratesandweresubjecttomoreseveredisturbances,leadingtoonlymodestCaccumulationsince1990.ThiswasparticularlyevidentintheRockyMountainRegion,whereforestswereaCsource(negativestockchange)in2019(Domkeetal.2021).6-30FutureofAmerica’sForestsandRangelandsFigure6-34.Forestremainingforesttotalforestecosystemcarbonstocksandstockchangesfor2019andprojectionsto2070foreachRPAscenario-climatefuture,byRPAregion.ProjectedforestecosystemcarbonstockandstockchangearebasedonaveragingdecadalprojectionresultsbyRPAscenario-climatefuture.NorthSouthRockyMntPacificCoastNotethatthey-axisvariesbyregion.ΔC=changeincarbonstocks;LM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.TheRockyMountainRegionisprojectedtoremainaCOtherLandConvertedtoForestsource,withdecreasingCstocksbetween2019and2070regardlessofRPAscenario-climatefuture(figure6-34).AspresentedintheLandResourcesChapter,forestlandcanbeConversely,theNorthRegionisprojectedtocontinuetoconvertedtootherusesandotherlandusescanbeconvertedbeaCsinkthroughouttheprojectionperiodunderallRPAtoaforestlanduse.Whenlandisconvertedtoaforestuse,scenario-climatefutures.IntheNorth,CstocksareprojectedtheConthatlandistransferredtothe“otherlandconvertedtocontinuetoincreasethrough2070,withannualstocktoforest”category(IPCC2006).Thetotalforestlandareaatachangeratesbetween2.1MMTCyr-1(HH-hot)and22MMTgiventimeisthesumoftheforestremainingforestareaandtheCyr-1(HL-wet).TheRPAPacificCoastandSouthRegionsotherlandconvertedtoforestarea.Historically,about1millionarebothprojectedtoexperienceCstockincreasesthroughhectaresofotherlandconvertstoforestannually,transferringmid-centuryacrossallRPAscenario-climatefutures.Cstocks27MMTCyr-1intotheforestlandbase(Domkeetal.2021);arethengenerallyprojectedtodecreaseundertheHHandLMhowever,forestareaisprojectedtodecrease(netforestloss)scenariosafter2050inthePacificCoastandafter2060intheovertheprojectionperiod,andtheamountoflandconvertedSouth,withbothregionsbecomingaCsource.UndertheHLtoforest(grossforestgains)isalsoprojectedtodecreasedueandHMscenarios,bothregionscontinuetoaccumulateCbuttothecompetitionbetweeneconomicreturnstoforestusesandatreducedstockchangeratescomparedto2019.economicreturnstootherlanduses.TheannualamountofCtransferredthroughconversiontoforestusesisprojectedtodecreaseby25to28percentbetween2019and2070undertheHLandHHscenarios,respectively.2020ResourcesPlanningActAssessment6-31HarvestedWoodCarbonandHHRPAscenariosandprojectedtoslightlydecreaseundertheHLscenarioduetothelowerprojecteddemandforCstoredinhardwoodproducts(HWP)andsolidwasteroundwoodproductsunderthisscenario(figure6-35b).SWDSdisposalsites(SWDS)contributessignificantlytotheforeststockchangeisprojectedtoincreaseacrossallRPAscenarios.landsectorsink(JohnstonandRadeloff2019).ThetrajectoryTotalharvestedwoodCisprojectedtoremainsmallrelativetooftheHWPCpoolintheUnitedStatesisdirectlytiedtothetheforestecosystempoolfrom2020to2070;however,globalamountofdomesticharvestandthetypesofproductsmadedemandforwoodproductsunderallRPAscenariosexceptHLfromthatharvest(seeForestProductsChapter).Similarly,isprojectedtoincreasethestockchangeinharvestedwoodSWDSCistiedtodomesticharvestandproducts,butitfrom29.6MMTCyr-1in2020tobetween36.9MMTCyr-1reflectstheCtrendsofproductsoncediscarded.Cstoredin(HM)and62.5MMTCyr-1(HH)in2070.UnderHL,CstockHWPandSWDS(totalharvestedwoodC)isprojectedtochangeinharvestedwoodisprojectedtodecreasefrom2020increaseovertheprojectionperiod(figure6-35a).Thestockto2030,thenslowlyreturnto2020levelsby2070.changeforHWPisprojectedtoincreaseundertheLM,HM,Figure6-35.Historicandprojectedtotalharvestedwoodcarbon(Cinharvestedwoodproductsandsolidwastedisposalsites)for(a)stocksand(b)stockchangefrom1990to2070,byRPAscenario.(a)HarvestedWoodCarbonStocks(b)HarvestedWoodStockChangeHarvestedwoodcarbonstock(billionmetrictons)Harvestedwoodcarbonstockchange(millionmetrictonsperyear)5806044032020200020252050200020252050YearYearHistoricLMHLHMHHC=carbon;LM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.Sources:ProjectionsforCinharvestedwoodproductsarebasedontheFOROMmodel(ForestProductsChapter,JohnstonandRadeloff2019).ProjectionsforCinsolidwastedisposalsitesarebasedonthemodelpresentedbySkog(2008).TotalCarbonforproductsunderHHisprojectedtobe1.6timeslargerthanunderLM,leadingtogreatertotalCstockchange.BasedontheTotalCincludesstocksandstockchangesfromtheforestprojections,harvestedwoodCstockchangeisexpectedtobeecosystem,harvestedwood,andotherlandconvertedtoforestlargerthantheforestecosystemstockchangeundereveryRPAcategories.TheforestecosystempoolisprojectedtoremainscenarioexceptHL,andthecontributionoftheharvestedwoodaCsinkunderallRPAscenariosexceptHH,whereCstockpooltototalCstockchangeisexpectedtoincreaseovertime.changeisprojectedtobe-16.2MMTCyr-1in2070(negativestockchangeisanetemissionofC).However,theCstockDriversofChangeinForestEcosystemCchangeinharvestedwoodislargeenoughtomorethanoffsetprojectedforestecosystemCemissionsunderHH(table6-5).TherearemanydriversofchangethatinfluencetrendsinforestWhenconsideringboththeforestecosystemandharvestedecosystemCstocks,includingbiological,socioeconomic,woodpools,Cstockchangeisprojectedtobepositiveacrossandclimatedrivers.ThegoalofthissectionistoanalyzetheallRPAscenariosin2070,althoughsignificantlylowerthanrelativeimportanceofthesedriversinforestecosystemC2019.TheHLscenarioisprojectedtohavethelargest2070futures.SocioeconomicdriversaffecttheamountofharvesttotalCstockchange,followedbyHM,HH,andLM.Whileforproducts,landusechange,andforestmanagement.LandtheLMscenariohasagreaterforestecosystemCstockusechoicesarealsosensitivetoclimatefutures(seetheLandchangethantheHHscenario,theincreasedforestharvestingResourcesChapter).Inaddition,forestecosystemCtrendsare6-32FutureofAmerica’sForestsandRangelandsTable6-5.Forestecosystemcarbon,harvestedwoodcarbon,andcarbonfromlandusetransferstoforestin2019andprojectedto2070,byRPAscenario.Stockchangesareprovidedinparentheses.DecadalprojectedvaluesfortheforestecosystemandlandusetransfertoforestaretheaverageofprojectionresultsbyRPAscenario.YearScenarioCarbonpool201920302040205020602070BMTC(MMTCyr-1)Forestecosystem45.35(155)46.89(145)47.86(97)48.37(48)48.35(20)48.18(1)Harvestedwood2.67(30)2.96(29)3.97(36)4.34(39)LMForestecosystem+harvested3.27(32)3.60(35)wood48.02(186)49.85(174)52.32(57)52.52(40)51.12(129)51.97(82)Otherlandconvertedtoforest--(27)--(24)--(23)--(22)--(21)--(20)Total48.02(213)49.85(198)51.12(152)51.97(105)52.32(78)52.52(60)Forestecosystem45.35(155)46.99(158)48.2(118)48.96(71)49.39(52)49.61(37)Harvestedwood2.67(30)2.95(27)3.22(28)3.51(29)3.81(30)4.11(30)HLForestecosystem+harvestedwood48.02(186)49.94(186)51.42(147)52.47(100)53.21(82)53.72(67)Otherlandconvertedtoforest--(27)--(25)--(24)--(23)--(22)--(21)Total48.02(213)49.94(210)51.42(170)52.47(123)53.21(104)53.72(88)Forestecosystem45.35(155)46.94(152)48.06(113)48.75(64)49.03(40)49.1(26)Harvestedwood2.67(30)2.96(29)3.27(32)3.59(34)3.94(35)4.31(37)HMForestecosystem+harvestedwood48.02(186)49.9(181)51.33(144)52.34(98)52.97(75)53.41(63)Otherlandconvertedtoforest--(27)--(24)--(24)--(23)--(22)--(20)Total48.02(213)49.9(206)51.33(168)52.34(121)52.97(96)53.41(83)Forestecosystem45.35(155)46.88(145)47.89(102)48.35(48)48.34(11)47.83(-16)Harvestedwood2.67(30)2.99(33)3.35(39)3.78(47)4.3(55)4.9(63)HHForestecosystem+harvestedwood48.02(186)49.87(178)51.24(142)52.13(95)52.65(66)52.74(46)Otherlandconvertedtoforest--(27)--(24)--(24)--(23)--(21)--(20)Total48.02(213)49.87(202)51.24(165)52.13(118)52.65(87)52.74(66)BMT=billionmetrictons;C=carbon;MMT=millionmetrictons;yr=year;LM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.influencedbybiologicaldynamicsandtheirinteractionwithFigure6-36.RelativeimportanceofRPAscenario,climateprojection,andRPAscenariosandclimateprojections.Biologicaldynamics,biologyinexplainingthedifferenceinforestecosystemCtrendsfrom2019toincludinggrowth,aging,increasedstocking,forestcomposition2070byRPAregion.shifts,andotherattributes,aresimulatedbytheForestDynamicsModel.WeexaminetheeffectsofthesevariousC=carbon.driversonforestcarbonstockfutures,isolatingtheinfluenceofscenario,climatemodel,andbiologicaldynamics.WeexaminedtherelativeimportanceofRPAscenario(LM,HL,HM,HH),climateprojection(leastwarm,hot,dry,wet,middle),and‘biologicaldevelopment’(biology)tothecumulativedifferenceinforestecosystemCovertheprojectionperiod(i.e.,thedifferencebetween2019CstockandCstockateachdecadaltimestep).Inthisanalysis,weusedchangeintimeasasurrogateforbiologysincethechangeintimereflectsbiologicalprocessessuchasforestgrowth,aging,anddisturbanceeffectsnotexplainedbytheotherfactors.Performingavariancecomponentsanalysis(McCullochandSearle2004)revealshowimportanttheRPAscenario,climatefuture,climateprojection,andbiologyeachareinexplainingtherangeofforestecosystemCstocktrends.AcrossRPAregions,biologywasthemostimportantcomponentinexplainingthecumulativechangeinforestecosystemCstocks(figure6-36).Thismakesintuitivesense2020ResourcesPlanningActAssessment6-33becauseforestshavedistinctgrowthpatterns,successionalFigure6-37.Historicandprojectedcarbonstocksforthemiddleclimatetrajectories,anddisturbanceregimes,allofwhichleadprojectionwithandwithoutanatmosphericenrichmentassumptionforthetopredictablebehaviorovertimeintermsofCstocks.HL,HM,andHHRPAscenarios.DecadalprojectionresultsarebasedonRPAscenariowasthesecondmostimportantdriverinallaverageacrossthe100realizationsfortheHL,HM,andHHscenariosfortheregionsexcepttheRockyMountainRegion,becauselandmiddleclimateprojection.usechangeandroundwoodharvestforproductsinfluencesCstocktrendsintheNorth,South,andPacificCoastRegions.TheclimateprojectionwasmoreimportantthanRPAscenariointheRockyMountainRegion(althoughnotnecessarilyaspecificclimateprojection),partiallybecausetheRockyMountainRegionisprojectedtohavethesmallestcontributiontoU.S.roundwoodproductionamongregions(andthusislessaffectedbyroundwooddemand),andpartiallyduetothelargeproportionofpublicforestlandintheregionresultinginlessprojectedlossofforestlanduse.AtmosphericEnrichmentHistoricAtmosphericEnrichmentNoAtmosphericEnrichmentTheForestDynamicsModeluseshistoricalbiologicalLM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highgrowthpatternstosimulatechangesinthefuture.However,warming-moderateU.S.growth;HH=highwarming-highU.S.growth.itispossiblethatbiologicalgrowthpatternscouldbeamplifiedorattenuatedbychangesinclimate.Atmosphericabout5.6percentlargerthanthoseprojectionswithoutenrichmentistheprocessbywhichelevatedlevelsofatmosphericenrichment.ThecumulativeeffectofatmosphericCO2andnitrogeneffectivelyfertilizeforests,resultinginenrichmentonthetotalamountofCsequesteredovertheincreasedgrowth(Fangetal.2014,Hemberetal.2012).Theprojectionperiodrangedfrom2.3to2.5BMTC,wherethescientificliteratureoffersarangeofgrowthenhancementlargestcumulativeeffectwasobservedundertheHHscenario.ratesduetoatmosphericenrichment,rangingfrom0to2percentperyear(WearandCoulston2015).AlthoughWithrespecttoCstockchange,atmosphericenrichmentdoesGreenandKeenan(2022),Jiangetal.(2020),Loetal.increaseratesbyabout22MMTCyr-1in2070andsuggestsa(2019),andWangetal.(2020)callatmosphericenrichmentfuturewhereU.S.forestecosystemswithineachRPAregionintoquestion,suggestingthattherearelimitstotheeffectareaCsinkundertheRPAscenarios.However,becauseCorthatthefertilizationeffectsaredeclining,thedegreetostockaccumulationslowsovertime,annualCstockchangewhichincreasedCO2influencesCstocksandfluxovertheratescontinuetodecreaseovertheprojectionperiod.Ourprojectionperiodisasourceofuncertainty.resultssuggestthatwhileatmosphericenrichmentcouldleadtofutureswithgreaterforestecosystemCstocks,stockswillToexaminethepotentialimpactsofatmosphericenrichment,increaseatadecreasingrate.weassumeda0.7percentperyearfertilizationeffectfortheRCP8.5RPAscenarios(HL,HM,HH),andusedtheDecadalprojectionresultsarebasedonaverageacrossthe100middleclimateprojectionasademonstration.AfertilizationrealizationsfortheHL,HM,andHHscenariosforthemiddlerateof0.7percentperyearwaschosenbecausepreliminaryclimateprojection.analysisoftheFIAdatasuggestedaneffectofthismagnitudeand0.7percentperyearwasintherangeofthepublishedManagementImplicationsliterature.BecauseCstockchangeratesareprojectedtoremainrelativelyconstantuntil2030,weappliedthegrowthTheforestsoftheUnitedStatesaremanagedforarangeenhancementbeginningin2030.Toimposetheatmosphericofobjectivesacrossarangeofspatialscales.ManagementenrichmentassumptionwithintheRPAForestDynamicsobjectivesincludemanagementforwaterqualityandquantity,Model,weartificiallyskewedmodeledforesttransitionswildlifehabitat,timberforproducts,recreation,andcarbon.overtimetowardsdenserandgenerallyolderstands.WhileOverthenext50years,managerswilllikelyexperiencetheforestaccumulatesCatafasterratewithatmosphericchallengeswithsimultaneouslymanagingfordifferentenrichment,otherprocessessuchasdisturbance,aging,andincreasedstockingcontinuetooccur.ThegrowthenhancementincreasedprojectedCstocksacrossRPAscenarios,andtheeffectoftheenhancementincreasedovertime(figure6-37).By2070,Cstockprojectionswere6-34FutureofAmerica’sForestsandRangelandsecosystemservicesanddevelopingbroad-scalemanagementscenarios,ourresultsdonotshowamanagementresponseapproachesinshiftingforestlandscapes.whereinvestmentsinforestryavoiddeclininggrowingstockvolumeattheendoftheprojectionperiod.WhileourresultsAtafine-scale(stand-level),therearesomeecosystemdosuggestanincreaseinplantedforestundertheLMandHHservicesthataredifficulttomanageforsimultaneously.Forscenarios,theincreasedoesnotoffsettheinfluenceofa39-toexample,managementtooptimizetimberproductionmaynot46-percentincreaseinforestharvested.Futuresconstructedoptimizewaterqualityandquantity.Similarly,managementwiththeForestDynamicsModelaccountforcontemporaryfocusedonmaximizingcarbonstoragemaynotbeoptimalformanagementapproaches(e.g.,planting,thinning,fertilization,wildlifehabitat.Understandingandmanagingforecosystemprescribedfire)commensuratewiththeforesttypes,standservicesoverabroaderspatialscaleisrequiredtodevelopandages,andownersthatdeploythem,butfutureimprovementsimplementasuiteofmanagementapproachestoincreasenettomanagementapproachesarenotincorporatedintheecosystemservicesanddecreasethepotentialeffectsofforestmodelingsystem.Increasingtheeffectivenessofthetoolsdisturbance.Thistypeofmanagementhasbeencontemplatedandapproachesavailabletoforestmanagers,whichcanbethrougheffortssuchastheUSDAForestService’sSharedfacilitatedthroughincreasedinvestmentinforestry,willhelpStewardshipstrategy.However,approximately60percentofmeettheincreasedroundwooddemandunderthesefutures.forestsacrosstheconterminousUnitedStatesareprivatelyInaddition,managementtoolsandapproachescanonlyowned.Mostfamily-ownedforestsdonothaveamanagementbenefittheforestlandwheretheyaredeployed,butmuchofplanandhencearepassivelymanaged.Further,U.S.foreststheNation’sforestlanddoesnothaveamanagementplan.existinamosaicofotherlandusesandlandcovers.CreatingIncreasingtheareawhereeffectiveforestmanagementisamechanismtoengagethedisparateownerswithdiversedeployedisacurrentandfuturemanagementchallenge.objectivestounderstandthepotentialopportunitiesofcollaborativeapproaches,acrosslandowners,toincrease,orManagementchoiceshaveimplicationsforcarbon-neutralityinsomecasesmaintain,theservicesthatforestsprovideisaeffortsandnaturalclimatesolutions.Csequestrationinthemanagementchallenge.forestsectorcurrentlyoffsetsapproximately11percentofemissionsfromothersectors(Domkeetal.2021).GiventhatTheresultspresentedinthischapter,coupledwithresultsfromprojectedforestsectorCsequestrationin2070isexpectedtheLandResourcesChapter,suggestthenext50yearswillbetodecreaseby59to72percent,othersectorswillneedtodynamic.LandusechoicesareexpectedtochangeoverthedecreaseCemissionsby95to97percentfortheUnitedStatesnext50years.Netforestarealossisprojectedinallregionstoachievecarbonneutrality.Naturalclimatesolutionsofferofthecountry;however,grossforestchange(forestloss+managementapproachestoenhancetheforestsectorCsink.forestgain)isprojectedtobesubstantiallylargerthannetThesesolutionsgenerallyfallintwocategories:maintainingchange.Whenconsideringgrossforestchange,itisimportantorincreasingforestextentandincreasingproductivitythoughtounderstandthatthecombinationoflossesandgainsmeansinvestmentsandchangesinforestmanagement.Giventheashufflingofwhereforestsexistonthelandscape,whoownsarealextentoftheforestlandbase(over600millionacresforthoseforests,andofthestructuralandcompositionalmakeuptheconterminousUnitedStates),naturalclimatesolutionswillofthoseforest.Further,asforestsshuffleonthelandscape,needtoaffectasignificantamountofforestlandtoshiftthethetypeandcompositionarelikelytobedifferentthantheprojectedCstocktrajectory,whichwouldhaveconsequencespersistentforestsinthelandscape.Broad-scalemanagementforotherecosystemserviceswhenconsideringthesebroad-approachesaimedatimprovingforestecosystemserviceswillscaleCobjectives.thereforeneedtoanticipateashiftingforestlandscape.ThisisparticularlyrelevanttoinitiativesthataimfornonetforestConclusionsloss,becauseoftentheforestsconvertedtootherlandusesaredifferentfromthoseareasthathaveafforested.TheimportantTheextensiveforestresourcesoftheUnitedStatesprovideconsiderationiswhethertherightforestsareintherightplacesawiderangeofgoodsandservicestotheAmericanpublic.tomeetbroad-scalemanagementobjectives.Sincethelate1970sforestareahasincreased,ashavegrowingstockvolumeandcarbonstocks.IncreasestotheIncreasingroundwooddemandhashistoricallyledtoforestlandbaselargelyarosebecauseforestgainsfromincreasedroundwoodprices,whichhavefacilitatedagriculturalabandonmentoutpacedforestlosstodevelopedinvestmentsinforestry.Previousforestryinvestmentsusesoverthelast50years.Despitedynamicshiftsinforestincludeddevelopingmoreeffectivesilviculturaltechniquesdisturbanceandtheireffects,theforestsoftheUnitedStatesandtreeimprovement,theadoptionofwhichresultedinahavecontinuedtosequesterCatratessufficienttooffsetCO2managementresponsethatincreasedforestproductivity.Ouremissionfromothersectors(e.g.,energy),providedtherawresultssuggestthatdemandforroundwoodcouldleadtomaterialfortraditionalforestproducts(e.g.,dimensionalfutureswhereharvestlevelsexceedthoseobservedfrom1976lumber),andprovidedtheresourcesforemergingmarketsto2016(LMandHHRPAscenarios).However,underthose(e.g.,pellets).Atthesametime,forestshavebeencriticalto2020ResourcesPlanningActAssessment6-35waterqualityandquantity,providingwildlifehabitat,andforestarea,theprojectedextentofforestremainshigherthanofferingrecreationalopportunities.observedinthe1980s.Further,growingstockvolume,whileprojectedtoincreaseatadecreasingrate,isexpectedtobeTheabilityofforeststoprovidethegoodsandservicesthatsubstantiallylargerin2070thanitwasin2020acrosstherangesocietydependsuponwillbechallengedoverthenext50ofroundwooddemandfutures.years.Globalandnationalpopulationandincometrendswillinfluencedemandforforestproducts,andtoalesserextentReferencesexpectedclimaticshiftswillinfluenceforestecosystemsintermsoftheircomposition,structure,andproductivity.Binkley,C.S.;Raper,C.F.;Washburn,C.L.1996.InstitutionalownershipIngeneral,theforestsoftheUnitedStatesareprojectedtoofUStimberland:history,rationale,andimplicationsforforestdecreaseinareabutincreaseinvolumeacrossRPAscenario-management.JournalofForestry.94(9):21–28.climatefutures.ProjectionssuggesttheincreaseinvolumewillbedrivenbyforestmaturationoutpacingtheeffectsofBirch,T.W.1996.Privateforest-landownersoftheUnitedStates,1994.disturbanceandharvestpressure.DespiteprojectedincreasesResour.Bull.NE-134.Radnor,PA:U.S.DepartmentofAgriculture,inforestvolume,growthratesareprojectedtoslow.TheForestService,NortheasternForestExperimentStation.183p.https://projecteddecreaseinyoungerforestssuggestsmuchofthedoi.org/10.2737/NE-RB-134.forestedlandscapewillshifttoanolderagecohortwhereforestecosystemCgrowth(stockchange)willbelessthanBurrill,E.A.;Wilson,A.M.;Turner,J.A.;Pugh,S.A.;Menlove,current(2020)estimates.ThedisparitybetweenactivelyJ.;Christensen,G.;Conkling,B.L.;David,W.2018.FIAdatabasegrowingyoungerforestandslowergrowingolderforestisdescriptionandusersguideforPhase2.Version7.2.U.S.Departmentofprojectedtoimpacttherangeofservicesforestsprovide,inAgriculture,ForestService.950p.https://www.fia.fs.usda.gov/library/somecasespositivelyandinothercasesnegatively.database-documentation/.(10May2019).RPAscenarios,asdrivenbydemandforroundwoodandlandButler,B.J.;Butler,S.M.;Caputo,J.;Dias,J.;Robillard,A.;Sass,E.useshifts,havebeenhighlightedasmoresignificantthan2021a.FamilyforestownershipsoftheUnitedStates,2018:resultsfromalternativeclimateprojectionsindefiningfutureconditionstheUSDAForestService,NationalWoodlandOwnerSurvey.Gen.throughoutthischapter.ThisresultdoesnotsuggestthatTech.Rep.NRS-199.Madison,WI:U.S.DepartmentofAgriculture,climaticshiftsarenotimportant;rather,ithighlightshowForestService,NorthernResearchStation.52p.https://doi.org/10.2737/theinfluenceofforestmanagementactivitiesoverbroadNRS-GTR-199.(8October2020).spatialscalesoccurringovershortertimeframesoutpacestheinfluenceofclimate.Moresimply,humansmayimpacttheButler,B.J.;Caputo,J.;Robillard,A.L.Sass,E.M.;Sutherland,C.forestsoftheUnitedStatesmorequicklythanclimateshifts.2021b.Onesizedoesnotfitall:relationshipsbetweensizeoffamilyHowever,thereareregionaldifferencesinthispattern.Theforestholdingsandlandownerattitudesandbehaviors.JournalofRockyMountainRegionistheonlyregionwheretheeffectsForestry.119(1):28–44.https://doi.org/10.1093/jofore/fvaa045.ofclimateprojectionovershadowtheprojectedeffectsofRPAscenario.TheRockyMountainRegioncurrentlyproduces,Butler,B.J.;Hewes,J.H.;Dickinson,B.J.;Andrejczyk,B.J.;Butler,andisprojectedtocontinueproducing,thesmallestshareS.M.;Markowski-Lindsay,M.2016.USDAForestServiceNationalofU.S.timberusedforproducts,whichsuggestslessforestWoodlandOwnerSurvey:National,regional,andstatestatisticsformanagement.ThesensitivityoftheRockyMountainRegiontofamilyforestandwoodlandownershipswith10+acres,2011–2013.Res.climateisdrivenbytheinteractionoffutureclimateswiththeBull.NRS-99.NewtownSquare,PA:U.S.DepartmentofAgriculture,conditions,typesofforestcommunities,anddisturbancesintheForestService,NorthernResearchStation.39p.https://doi.org/10.2737/region.Ourprojectionssuggesttheconcurrenteffectsofthesenrs-rb-99.(8October2020).interactionsisastrongerdriverthandemandforroundwoodandlandusechange.Butler,B.J.;Wear,D.N.2013.Forestownershipdynamicsofsouthernforests.In:Wear,D.N.;Greis,J.G.2013.TheSouthernForestFuturesTheresultspresentedhererepresentarangeofdifferentProject:technicalreport.Gen.Tech.Rep.SRS-GTR-178.Asheville,projectedtrends.Withrespecttoforestarea,projectionsNC:U.S.DepartmentofAgriculture,ForestService,SouthernResearchsuggestatrendreversalfromhistoricincreasesinforestareaStation:103–121.toafuturewithdecliningforestarea.GrowingstockvolumeandforestecosystemCstocksareexpectedtofollowcurrentButler,S.M.;Butler,B.J.;Schelhas,J.2020.Minorityfamilyforest(increasing)trendsthrough2030.From2030to2070,theseownersintheUnitedStates.JournalofForestry.118(1):70–85.https://increasestobothvolumeandcarbonoccuratadecreasingdoi.org/10.1093/jofore/fvz060.(slower)rate.Theslowerrateofcarbonaccretionpost-2030leadstoashiftfromtherelativelystatic1990to2020forestCoulston,J.W.;Wear,D.N.;Costanza,J.;Brooks,E.B.;Walker,D.ecosystemCstockchangeratetrendtoadecreasingtrendin[Inpreparation].ProjectingtheforestdynamicsoftheUnitedStates:aannualCstockchange.WhilethereareprojecteddecreasesinmethodsdocumentsupportingtheForestService2020RPAAssessment.Davis,L.S.;Johnson,K.N.1987.ForestManagement.3rdedition.NewYork:McGraw-Hill.790p.Domke,G.M.;Walters,B.F.;Nowak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forgraphicsFrom2017to2020,theUnitedStatesanditsforestproductspaper(Brandeisetal.2021).sectorwereaffectedbyincreasesintradebarriers,bothonimportsintotheUnitedStates(particularlyfromCanada)Hardwoodproductsalsoshowtemporalvariationsinandexportsfromthiscountrytomanyofitsmajortradingproduction,consumption,andtrade,relatedtotheU.S.partners,suchasEuropeandChina(Panetal.2021).andglobalrecessions,butseculartrendsinconsumptionAlthoughthereisuncertaintyaboutthefutureevolutionandproductionhavedominated.TheUnitedStatesisaoftradefrictions,thescenario-basedapproachusedinnetexporterofhardwoodlumber,connectedinparttothethisAssessmentprovidesforarangeofpossibletariffoffshoringoffurnituremanufacturinginthe1990sand2000senvironments,likelybracketingmuchofthatuncertainty.andcorrespondinggrowthinoverseasfurnitureproduction(e.g.,Grusheckyetal.2006,SchulerandUrs2003).ByToday,thenationandtheworldareemergingfromthe2019,consumptionofhardwoodlumberintheUnitedStatessharpesteconomiccontractionsincetheGreatDepression,haddeclinedbynearly40percentsinceits1999peak,aduetotheSARS-CoV-2globalpandemic.ThebaseyearofresponsetothedisinvestmentintheNation’swoodfurnitureourprojectionscenariofallsbeforethepandemicandourmanufacturingsector.U.S.hardwoodindustrialroundwoodfocusisonlong-runprojections,sotheresultswepresentdotrendshavebeensimilarlyimpactedbytheshiftsinglobalnotdirectlyincorporatethesharp,short-termdynamicsinthewoodfurnituremanufacture,particularlytoAsia.economythatbuffetedthesector.However,asidebarofthischapterdoesevaluatesomeofthedynamicsandpotentialAsWearetal.(2016)pointout,long-termtrendsintheU.S.forestsectorarerevealednotjustinmarketsforforestFigure7-1.U.S.productionandconsumptionofindustrialroundwood,productsbutalsoinitsdemandsforinputs,includinglabor,nationwide,1961to2019.capital,andwood.EmploymentinthewoodproductsandpapersectorhasbeentrendingdownwardforseveraldecadesConiferousIndustrialRoundwoodProductionConiferousIndustrialRoundwoodConsumption(Wearetal.2016).TheemploymenttrendsaccompanyrisingNonconiferousIndustrialRoundwoodProductionNonconiferousIndustrialRoundwoodConsumptioncapitalintensificationandtechnologychanges.Thehigherefficienciesinbothlaborandwoodfiberuse(Brandeisetal.Source:FAO2021.2021)havebeenenabledbyinnovationsinmanufacturingtechnologyfavoringcapitaloverlabor.TheefficiencygainsarefurtherpairedwiththebroadmoveawayfrompaperasamediumforinformationdeliveryandthedeclininguseofpaperperunitofoutputbytheU.S.manufacturingsector.OnefeatureoftheU.S.forestproductmarket,whichcanbedescribedasanelementofthesector’smultipletrendsbutwithanuncertainlong-termtrajectory,hasbeentherapidgrowthintheproductionandexportofwoodpelletsforenergy.Althoughpelletsrepresentasmallfraction(lessthan7-2FutureofAmerica’sForestsandRangelandsAShort-TermAnalysisofCOVID-19ontheU.S.ForestProductMarketsTheseconddecadeofthe21stcenturyendedwithaglobalthan2015,thestartingpointofthemainchapter)and,inpandemiccausedbytheSARS-CoV2virusandtheillnessplaceofscenario-basedprojections,usetheannualgrossitproduces,COVID-19.Tocontainthespreadofthevirus,domesticproduct(GDP)forecastsoftheOrganizationforgovernmentsimplementedstrictlockdownregulationsEconomicCooperationandDevelopment(OECD)forthewhich,alongwithfearsofcontractingtheCOVID-19world(OECD2020)andU.S.CongressionalBudgetOfficeillness,shrankeconomicactivitytolowsnotexperienced(CBO)fortheUnitedStates(CBO2020).TheOECDandindecades.ForestproductmarketswereamongthoseCBOforecastsforGDPenvisioneda“V-shaped”recoveryexperiencingsubstantialdisruptionsearlyinthepandemic,path.Themodelingpresentedherealsoabstractsfromendingaslowbutsteadyriseineconomicoutputinthethemainchapterbynotinteracting(harmonizing)withUnitedStatesandgloballyfromthe2007to2009globaltheRPAForestDynamicsModelinidentifyingmodelfinancialcrisis.Despiteexperiencingsomedisruptionssolutions.Variationsonthescenario,C19-3,C19-6,andearlyon,theU.S.forestproductssectorreboundedquickly,C19-8,quantifytheeffectsunderalternative2020U.S.GDPyetthesectorexhibitedbehaviorsuniquetothevirusandannualgrowthratesof-3percent,-6percent,and-8percent,differedfromtypicalrecessions.Thissidebarplacesintorespectively.ToidentifytheneteffectofCOVID-19oncontextthescaleofthepandemic’simpactsonforestthesector,wecomparedC19-3,C19-6,andC19-8withaproductmarketsandinformshowsuchshort-runmarketpre-COVID-19projectionoftheU.S.andworldeconomydynamicsmightbeconnectedtothelong-rundynamicsmadebyCBOandOECDfor2020and2021.AssumeddescribedinthemainpartoftheForestProductsChapter.GDPgrowthfrom2022to2030staysthesameforallthescenarios,correspondingtoOECD’spre-pandemicTocharacterizetheimpactsofthepandemiconthesector,projections(OECD2020).Projectionsareto2030,andourweappliedanannualizedversionoftheFOrestResourceanalysisfocusesparticularlyonlumbermarkets.OutlookModel(FOROM)model,whichcontainstheessentialfeaturesoftheperiodicFOROMmodelusedAccordingtotheprojections(figure7-2),COVID-19hasincarryingoutthelong-runprojectionsreportedinthetime-varyingimpactsonlumbermarkets.Softwoodlumbermainbodyofthechapter.Incarryingoutwhatwelabelconsumption,afteraninitialdrop,quicklyreboundsandaCOVID-19scenario(abbreviatedC19infigure7-2),aexceedswhatitwouldhavebeenwithnoCOVID-19.keymodificationhasbeenmadetoaccommodateashorterThedifferenceincreasesto2.2to3.5millionm3by2030.runanalysiscomparedtowhatwasundertakeninthemainHardwoodlumberconsumption,incontrast,isprojectedchapteronforestproducts.Todothis,wefirstupdatedtoremainbelowtheno-COVID-19counterfactuallevelthestartingconditionsoftheprojectionsto2018(ratherafteritsinitialdrop,1.1to1.7millionm3lessin2030.TheFigure7-2.Historic(1990to2019)andprojected(2020to2030)U.S.lumberconsumption,forsoftwood(left)andhardwood(right).SoftwoodU.S.LumberHardwoodU.S.LumberC19-3=2020U.S.GDPannualgrowthrateof-3percent;C19-6=2020U.S.GDPannualgrowthrateof-6percent;C19-8=2020U.S.GDPannualgrowthrateof-8percent.2020ResourcesPlanningActAssessment7-3combinedeffectsofthechangesinlumberconsumptionnear-normallevels3to4monthsaftertheUnitedStatesaretosomeextentconsistentwithBuongiorno(2021).firstenteredintoabroadlock-downnationwideinMarch2020tolimitvirusspread(USDAFAS2021).DespitetheInlinewiththeanalysisintheForestProductsChapter,rapidincreaseinwoodproductsdemandfollowing3tothecounterfactualanalysisinthissidebarshowsthatthe4monthsofsubduedactivity,thewoodproductssectorsupplyofanddemandforforestproductshingeonoverallhasnotprovedimmunetothemultifacetedimpactsofnationaleconomicgrowth.Therateoftheeconomicthepandemic.Producerswereunabletorespondtohighgrowthfollowingthe2020nadirinconsumptionaffectsdemandpromptlyduetolaborshortagesandjumbledtowhatextenttheforestproductmarketmayexhibitglobalsupplychains(Riddle2021),whichconstrainedpermanentimpactsfromthepandemic.Asharperbutproductioncombinedwitharelativeabundanceofshorter“V-shaped”recoverymakesupforthepreviousstandingtimbervolumesinmuchofthecountry—dropingrowthandallowstheproductionandconsumptionparticularlyintheSouthernUnitedStates—andtheseofforestproductstoreturnclosetoitslong-runtrend.Infactorscombinedtokeeptimberpriceslow(TimberMart-contrast,alongerperiodofU-shapedrecoveryreducestheSouth2021).Wecautionthatthissidebarisnotintendedtoproductionandconsumptiontoapermanentlylowerlevelbeexhaustiveofitseffectsofthepandemiconthesector;comparedtotheresultsbasedontheperiodicFOROM.instead,itisprovidedtogivearough,firstapproximationofhowitalteredmarketconditions.Additionally,theThissidebarhighlightsthepotentialmulti-yearresponsessimulationresultsarenotintendedtoofferpredictionsofofforestproductmarketstoCOVID-19disruptions.futuremarketconditionsbutinsteadareofferedtoquantifyEvidenceavailabletodayindicatesthattherewereearlyhowthepandemicaffectedmarkets.significantdisruptionsinthewoodproductssector,butdomesticU.S.productionandimportsslowlyreturnedto2percent)ofallroundwoodconsumed,woodpelletshavetrenddownwardinthenumberofhousingunitsbuilt,whichgrownrapidly,destinedfortheEuropeanUnion(EU)incouldbeconnectedtoaslowingU.S.population(U.S.Censussupportofthatregion’srenewableenergypolicies.Bureau2021a,Prestemonetal.2022)andaslowingoverallU.S.economyovertime(e.g.,Gordon2016).ToseehowTheU.S.housingmarket(figure7-3),akeycomponentoftheprojectionsinthischapterlinktolandusechange,whichwoodproductsdemand,hasdependedinpartonagrowingU.S.embodiesthenewhousingconstructiontrends,seethesidebarpopulationandeconomy.Housingstarts,inbothsingle-familyTheFOrestResourceOutlookModel(FOROM).andmultifamilyunits,havetrendeddownwardsinceWorldWarII,althoughbothcategoriesarehighlyvariable(U.S.CensusAfinallong-termtrendintheforestsectorconcernsBureau2021b).Prestemonetal.(2018)foundalong-termclimate(Tianetal.2016).Asgreenhousegases(GHGs)accumulateintheatmosphere,temperaturesarerisingandFigure7-3.U.S.single-familyandmultifamilyhousingstarts,1959to2020.precipitationpatternsarechanging.AlongwiththehigherGHGconcentrationsandhighertemperaturesisageneralriseTotalUnitsSingle-familyMultifamilyinnetgrowthofforests,particularlywhensufficientwaterSource:U.S.BureauoftheCensus2021.isavailabletofacilitateanaccelerationinphotosynthesis.Globally,forestproductivityisexpectedtorisewithalteredGHGconcentrationsandhighertemperatures.Suchproductivityrisescouldaffectmarketsindiverseways,includingintheUnitedStates.Withhighertemperaturesandthehigheroverallatmosphericwatercontentthatthesehighertemperaturesenable,analystsexpectchangesinthefrequency,intensity,spatialextent,anddurationofnaturaldisturbances,includingfrominsects,diseases,tropicalcyclones,wildfires,anddroughts(seetheDisturbanceChapter).Suchdisturbancechangesmaycountersomeoftheclimateforcingofforestproductivity,andlarge-scaleeventscanleadtomarketchanges(e.g.,PrestemonandHolmes2000,2004).Thefuturemarketoutlookforforestproductswasprojectedfrom2020to2070—basedona2015baseline—forthefour7-4FutureofAmerica’sForestsandRangelandsfutureRPAscenarios(seethesidebarRPAScenarios,aswelltheForestResourceOutlookModel.FOROMincorporatesastheScenariosChapterformoreinformation),withthevariousassumptionsonsocioeconomicdevelopmentsRPAclimateprojectionsincorporatedthroughforestinputsconsistentwiththeSSPs,andcertainclimaticinfluencesonfromtheForestDynamicsModel(seethesidebarTheFOresttheglobalforestsectorconsistentwiththeRCPs.ThesidebarResourceOutlookModel).ThesefuturescenariosprovideaFOrestResourceOutlookModel(FOROM)elaboratesonframeworkfordescribingaplausiblerangeintheevolutionhowthefourRPAscenariosweresimulatedwithinFOROM;ofglobalforestproductmarkets.Whenpresentingthethoselookingformoredetailedinformationareencouragedresults,itissometimesrequiredtoprovideadditionaldetailtoreviewJohnstonetal.(2021).atthecountry/regionalorproductlevel.Intheseinstances,theHMscenario(highwarming-moderateU.S.growth)isForamorein-depthoverviewofthestateoftheU.S.forestusedbydefaultasitalignscloselywiththeSSP2“middle-productssector,refertootherRPAproducts,includingStatusof-the-road”pathway,wheremanyoftheindicatorsbroadlyandTrendsfortheU.S.ForestProductsSector(Brandeisetfollowhistoricaltrendsthrough2070.al.2021).AdditionalcontextabouttheUnitedStatesaspartoftheglobalforestproductssectorisavailablefromWearetThefutureevolutionoftheU.S.andglobalforestproductsal.(2016)andPrestemonetal.(2015).sectorconsistentwiththeRPAscenarioswasmodeledusingRPAScenariosTheRPAAssessmentusesasetofscenariosofcoordinatedFigure7-4.Characterizationofthe2020RPAAssessmentscenariosfutureclimate,population,andsocioeconomicchangetointermsoffuturechangesinatmosphericwarmingandU.S.projectresourceavailabilityandconditionoverthenext50socioeconomicgrowth.Thesecharacteristicsareassociatedwithyears.ThesescenariosprovideaframeworkforobjectivelythefourunderlyingRepresentativeConcentrationPathway(RCP)–evaluatingaplausiblerangeoffutureresourceoutcomes.SharedSocioeconomicPathway(SSP)combinations.The2020RPAAssessmentdrawsfromtheglobalSource:Langneretal.2020.scenariosdevelopedbytheIntergovernmentalPanelonClimateChange(IPCC)toexaminethe2020to2070modelprojectionsisnotusedbecauseoftheimportancetimeperiod(IPCC2014).TheRPAscenariospairtwoofpreservingindividualmodelvariabilityforresourcealternativeclimatefutures(RepresentativeConcentrationmodelingefforts.ThefiveclimatemodelsselectedbyRPAPathwaysorRCPs)withfouralternativesocioeconomicrepresentleastwarm(MRI-CGCM3),hot(HadGEM2-futures(SharedSocioeconomicPathwaysorSSPs)inES),dry(IPSL-CM5A-MR),wet(CNRM-CM5),andthefollowingcombinations:RCP4.5andSSP1(lowermiddle-of-the-road(NorESM1-M)climatefuturesforthewarming-moderateU.S.growth,LM),RCP8.5andSSP3conterminousUnitedStates;however,characteristicscan(highwarming-lowU.S.growth,HL),RCP8.5andSSP2varyatfinerspatialscales.Althoughthesamemodelswere(highwarming-moderateU.S.growth,HM),andRCPselectedtodevelopclimateprojectionsforbothlower8.5andSSP5(highwarming-highU.S.growth,HH)andhigh-warmingfutures,distinctclimateprojectionsfor(figure7-4).Thefour2020RPAAssessmentscenariosencompasstheprojectedrangeofclimatechangefromtheRCPsandprojectedquantitativeandqualitativerangeofsocioeconomicchangefromtheSSPs,resultinginfourdistinctfuturesthatvaryacrossamultitudeofcharacteristics(figure7-5),andprovidingaunifyingframeworkthatorganizestheRPAAssessmentnaturalresourcesectoranalysesaroundaconsistentsetofpossibleworldviews.TheScenariosChapterdescribeshowtheseclimatemodelswereselectedandpaired;moredetailsareprovidedinLangneretal.(2020).The2020RPAAssessmentpairsthesefourRPAscenarioswithfivedifferentclimatemodelsthatcapturethewiderangeofprojectedfuturetemperatureandprecipitationacrosstheconterminousUnitedStates.Anensembleclimateprojectionthataveragesacrossthemultiple2020ResourcesPlanningActAssessment7-5eachmodelareassociatedwithRCP4.5andRCP8.5.TheincorporatedtheeffectsofclimateonforestsgloballyisScenariosChapterdescribeshowtheseclimatemodelsshowninthesidebarFOrestResourceOutlookModelwereselected.JoyceandCoulson(2020)giveamore(FOROM)andmoreextensivelyinJohnstonetal.(2021).extensiveexplanation.AnexplanationofhowtheFOROMFigure7-5.Characteristicsdifferentiatingthe2020RPAAssessmentscenarios.ThesecharacteristicsareassociatedwiththefourunderlyingRepresentativeConcentrationPathway(RCP)–SharedSocioeconomicPathway(SSP)combinations.FOrestResourceOutlookModel(FOROM)TheFOrestResourceOutlookModel(FOROM)isaFOROMincorporatesvariousassumptionstohelpshapepartialequilibriummodeloftheworld’sforestsectorfutureconditions.Themaindriversoftheevolutionofthatincludesforestresources,timbersupply,demandfortheglobalforestsectorincludeexogenoustrendsingrossintermediateandfinalproducts,andinternationaltrade.domesticproduct(GDP)andpopulation.MarketdemandThemodeliscalibratedprimarilytotheFAOSTAT(FAOisassumedtochangeovertimethroughexogenousshiftsStat2021)2015baseyearinformation,supplementedwithinGDPpercapita,whilechangesinpercapitaGDPaffectinformationfromtheU.S.DepartmentofAgriculture,themarginalcostofproductionarisingthroughchangesinForestService’sTimberProductOutput(TPO)programforestareaandstandinginventory.andtheUnitedStatesInternationalTradeCommission.ThemainfunctionofthismodelistoanalyzewhetherandOtherexogenousassumptions,includingtechnologicaltowhatextentproduction,consumption,trade,andpricesdevelopment,providethedegreewithwhichtheglobalofrawmaterial,intermediates,andfinalproducts,aswellforestsectorbecomesefficientintransformingrawasforestlandareaandforeststandingstock,mightchangematerialsintofinishedproducts.Tradeopennessdescribesinresponsetoexternalshockssuchaseconomicgrowth,thefrictionsembeddedinthemodelrelatingtotheclimatechange,tradeliberalization,orforestmanagement.movementofgoodsbetweenforeignregionsofthemodel.Inaddition,thedemandforbioenergyiscalibratedto7-6FutureofAmerica’sForestsandRangelandsprojectionsofprimaryandsecondarybiomassenergyfromreplacedbythosemadebytheRPAForestDynamicstheInternationalInstituteforAppliedSystemsAnalysisModel(FDM).FDMprojectionswereaveragedacrossIntegratedAssessmentModelingframework,reflectingtheRPAclimateprojections(leastwarm,hot,dry,wet,plausibledifferencesinthefutureevolutionofpreferencesmiddle)foreachRPAscenarioandeachprojectiontime-(seeBaueretal.2017).step.ProjectionsoftheU.S.forestsectormadejointlywithFOROMandtheFDMwereharmonizedoninventoryToevaluatetheforestsectorimpactsofclimate(volume)andremovals(roundwoodproduction)tofindachange,exogenouslyprojectedchangesinnetprimaryroundwoodpricepathwheretheinventoryandremovalsproductivity(NPP)wereusedintheFOROMtoadjustthefortheUnitedStatesalignedovertheprojectionperiod.Inendogenoussupplycostsofeachcountry/regionoutsideeach5-yeartimestepofFOROM,theFDMwasusedtotheUnitedStates.ChangesinNPPweresimulatedtocalibrateinventorygrowthratesacrosstheRPAregions,2070at0.5degree-resolutiongloballybythedynamicwhichwereanexogenousinputintoFOROM.Then,globalvegetationmodelMC2(Kimetal.2017),basedFOROMprojectedanendogenouspathofremovalsandonclimatechange(precipitationandtemperature)androundwoodprices.TheroundwoodpriceswerethenusedCO2(atmosphericforcing)changeinputs.ClimateandintheFDMharvestchoiceandtimbersupplymodelstoCO2changeinputstoMC2inKimetal.(2017)wereprojectremovals.TheprojectedremovalsfromFOROMobtainedfromtheMITIntegratedGlobalSystemModel-andtheFDMwerethencomparedtoensurealignment.CommunityAtmosphereModel(IGSM-CAM)forRCP4.5(correspondingtotheLMscenario)andRCP8.5(HL,HM,Table7-1providesanoverviewofthedefiningandHHRPAscenarios).MC2projectionsunderRCP8.5characteristicsoftheRPAscenarios.wereaveragedacrossallsevenensemblemembers(sevenclimatesimulations)reportedbyKimetal.(2017),whileAsGDPandpopulationarekeytotheevolutionofmarketRCP4.5wasprojectedwithasingleclimatesimulationprojectionsinFOROM,theyreceivedspecialattentionfromthatstudy.NPPprojectionsmadebyMC2wereinthe2020RPAAssessment.First,WearandPrestemonaggregatedto16globallandunits(countriesorregions),(2019)developedamethodtojointlydownscalenational-andtheiraverageannualtrendswereconvertedtochangesscaleincomeandpopulationprojectionstocountiesinforestproductivityabovebaseratesofgrowthforeachnationwide.Thismethodwasdesignedthroughstatisticalcountryassignedtooneofthegloballandunits.estimationoftherelationshipsbetweenhistoricalpersonalincomepercapitaatthecountyscaleandpopulationattheWhensolvingforglobalforestsectorsolutionsofthecountyscale.DownscalingwasdonesuchthatthesumofFOROM,however,climate-inducedproductivitychangeincomeandthesumofpopulationacrosscountiesmatchedprojectionsmadebyMC2fortheUnitedStateswerethenationallevelincomeandpopulationprojections,Table7-1.KeyexogenousdriversofglobaltrendsintheRPAscenarios.RPAscenariosExogenousdriverLMHMHLHHSocioeconomicHighinLICs,MICs;ModerateLowHighGDPmoderateinHICsLowinOECD,highinHighinOECD,lowinModeratePopulationRelativelylowModerateothercountriesothercountriesModerateLowHighTechnologicalchangeHighModerateLowHighLowHighTradeopennessModerateHighHighHighBioenergypreferencesHighSSP2RCP8.5SSP3SSP5ClimaticRCP8.5RCP8.5AtmosphericwarmingLowMotivatedbythefollowingIPCCscenariosSSPSSP1RCPRCP4.5GDP=grossdomesticproduct;HIC=highincomecountry;LIC=lowincomecountry;MIC=middleincomecountry;OECD=OrganizationforEconomicCooperationandDevelopment;RCP=RepresentativeConcentrationPathway;SSP=SharedSocioeconomicPathway;LM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.2020ResourcesPlanningActAssessment7-7respectively,foreachofthefiveSharedSocioeconomicFigure7-6.ResourcesPlanningActregionsandsubregions.Pathways;archiveddatasetsareavailablefromWearandPrestemon(2019).Next,togenerateprojectionsofearlystagesofdevelopment(e.g.,masstimber).ResearchGDPandpopulationattheRPAregionlevel,asimpleonnewproductsisongoing,andsomeareconsideringhowaggregationwasdonebysummingprojectedpersonalthesenewproductsmayenterintomodelslikeFOROMincomeandprojectedpopulationacrossallcounties(foranexample,seeNepaletal.2021whoexplorevariousassignedtoeachRPAregion.scenariosofintegratingmasstimberintoFOROM).FOROMexplicitlyrecognizestheUnitedStatesassixdistinctRPAregions,separatingtheRPANorthandSouthRegionsintotheircomponentsubregionsforaddedspecificity(seefigure7-6).Theregionaldetailallowsthemodeltodirectlyaccountforchangesinforestconditionsandlandusesandassociateddifferencesinregionalproductionanddemandconditions,includingthoseemergingfromindependentprojectionsofGDPandpopulationfromWearandPrestemon(2019).FormoredetailedinformationonFOROM,seeJohnstonetal.(2021).ItisimportanttonotethatmodelslikeFOROMarecalibratedtoexistingdata,andparameterizedbasedonhistoricalrelationshipswithexistingproductmarkets.Thus,asalimitation,thesemodelscannotpredicttheinventionofnewproducts,orproductsthatmaybeintheirGlobalTrendsandProjectionsThissectionsummarizesthemarkettrendsandFOROM-basedglobalmodelingresultsformajorforestproducts(e.g.,❖Globalforestproductsmarketshavebeenfuelwoodandindustrialroundwood)undertheRPAscenarios.Historicaldataonthequantitiesofproduction,imports,graduallyrecoveringfromthedeeprecessionexports,andunitvaluesofproductsareavailablefromof2007to2009.FOROMprojectsthatglobalBrandeisetal.(2021)fortheUnitedStatesandfromFAOStatsoftwoodroundwoodconsumptionreturnstopre-(2021),whichprovidedtheinputdatafortheglobalmarketrecessionlevelsby2020andcontinuestogrowmodel,FOROM.GlobalandU.S.projectiondataforthisthereafter.ThehardwoodindustrialroundwoodassessmentareavailablefromJohnstonetal.(2022).consumptiontrendresemblesthatofsoftwoodbutwithahighergrowthrate.Therealpricesforsoftwoodandhardwoodindustrialroundwoodareprojectedtoincreasefrom2020to2070❖Economicgrowthinemergingeconomiessuchas(figure7-7).ThepricesexhibitlargevariationsacrosstheRPAscenarios,whicharemostlydrivenbydifferencesinChinaandIndiadrivemuchoftheoverallgrowththeGDPdevelopments.Thepriceofsoftwoodindustrialindemandforindustrialroundwoodacrosstheroundwoodproductsisexpectedtoseethelargestgrowthscenarios.undertheRPAHHscenario,risingfrom$90.91perm3to$210.63perm3.Incontrast,theHLscenario,whichfeatures❖TheconsumptionandproductionofnewproductsalowGDPgrowthrate,isexpectedtoseethelowestlevelsofpricegrowth.Priceelasticitiesofdemandforhardwoodsuchaswoodpelletshavethepotentialtoare,onaverage,relativelysmallerthanthatofsoftwood;increasesignificantlyovertheprojectionhorizontherefore,alargerpriceriseisneededtosatisfythedemandundersomescenariosbutarecontingentuponforhardwoodindustrialroundwood.Socioeconomicpolicyassumptions.conditions,however,leadtothesamegeneralpatternofhardwoodindustrialroundwoodpricegrowth,withHH❖TherehavebeenmajorstructuralchangesingeneratingthehighestandHLthelowest.marketsforsomewoodproductcategoriesThedemandforbioenergyintheformoffuelwoodaswellsincethedeeprecessionof2007to2009,aswoodpelletsinFOROMareassumedtobedrivennotincludingmarketsfornewsprintandprintingandwritingpaperwhichhaveexperiencederosionindemandbecauseofthegrowthindigitalalternatives.7-8FutureofAmerica’sForestsandRangelandsFigure7-7.Projectedaveragepricesforglobalsoftwoodindustrialroundwood(left)andhardwoodindustrialroundwood(right)byRPAscenario,2020to2070,relativeto2015averageprices.SoftwoodIndustrialRoundwoodHardwoodIndustrialRoundwoodLMHMHLHHHistoricLM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.onlybyeconomicdevelopmentassumptions,butalsobyFOROMisdrivennotonlybychangesinGDPpercapita,differencesinconsumerpreferenceandpolicyassumptionsbutisalsoconstrainedusingtrendsinglobalsecondaryunderpinningtheIPCC’sSharedSocioeconomicPathwaysbiomassenergyproductiontocaptureSSP-relatedpreference(Baueretal.2017).Forfuelwooddemand,FOROMandpolicydifferences(figure7-9).GlobalgrowthratesofincorporatestrendsconsistentwithglobalprimaryenergysecondaryenergywereusedtoscalerecentregionalgrowthfrombiomassfromtheIPCCSSPscenarios(figure7-8).rates.Secondaryenergyisenergythathasbeenconverted,Similarly,theevolutionofwoodpelletconsumptioninandinthecaseofbioenergy,thiscouldrepresentenergysourcedfrombiomassincludingwoodpellets.Figure7-8.GlobalprimaryenergyproductionfortheIPCCSharedSocioeconomicPathwaysusedintheRPAAssessment.SSP1SSP2SSP3SSP5Exajoules1,6001,6001,6001,6001,4001,4001,4001,4001,2001,2001,2001,2001,0001,0001,0001,00080080080080060060060060040040040040020020020020000002005204020602005201020202030204020502060207020052010202020302040205020602070200520102020203020402050206020702020BiomassOtherrenewablesNuclearOilGasCoalIPCC=IntergovernmentalPanelonClimateChange;SSP=SharedSocioeconomicPathway.Source:Riahietal.2017.2020ResourcesPlanningActAssessment7-9Figure7-9.GlobalsecondaryenergyproductionfortheIPCCSharedthroughoutthesimulation.ThefuturepriceprojectionofSocioeconomicPathwaysusedintheRPAAssessment.hardwoodfuelwooddoesnotquiteresemblethetrendsofsoftwoodfuelwoodbecauseitspositiveincomeeffectonExajoulesdemandismitigated,tosomeextent.Thus,thegrowthrateofglobalaveragehardwoodfuelwoodpriceissmallerthanSSP1SSP2SSP3SSP5thatofsoftwoodfuelwoodpriceforthesamescenario.IPCC=IntergovernmentalPanelonClimateChange;SSP=SharedSocioeconomicPathway.Overthepastdecade,theworldhasexperiencedaboomSource:Riahietal.2017.inwoodpelletsmarkets.Globalwoodpelletconsumptionreached35.4millionmetrictons(mt)in2018,moreToillustratetheprojectionsofbioenergydemandunderthethandoubleits2010levelsof13.5millionmt.EuropeisRPAscenarios,considerthesustainability-mindedSSP1theworld’slargestwoodpelletproducerandconsumer,scenariothatunderpinstheRPALMscenario.Here,globalmainlyowingtoEU’sbindingrenewableenergytargetsaveragefuelwoodconsumptionreachesitshighestlevels,for2020and2030,andotherenvironmentallegislation.Indriveninpartbystrongeconomicgrowth,butalsofrom2018,theEUconsumed26.1millionmtofwoodpelletsimpliedenvironmentalandpolicysupport.Correspondingly,butproducedonly20.1millionmt.ThegapbetweenthewecanseethatintheLMscenario,thepriceoffuelwoodsupplyanddemandwithintheEUiscontributingtotherisesrapidlyandpeaksin2050(figure7-10).Aspreferencesincreasingimportanceofglobalwoodpellettrade.In2018,tendtoshiftmoretowardwoodpellets,demandforfuelwoodintercontinentaltradeinwoodpelletsamountedto29millionisgraduallydecreasing,resultinginapricedrop.Incontrast,mt,ofwhichmorethanhalf(17millionmt)wasimportedtheglobalaveragesoftwoodfuelwoodpriceintheHHfromtheUnitedStatesbytheUnitedKingdom.scenario—afossilfuel-dominatedworld—isexpectedtoremainrelativelyunchanged.EventhoughthereisanegativeTheRPAHLscenarioistheonlyscenarioinwhichglobaldemandgrowthintheearlyperiod,thenegativeimpactiswoodpelletconsumptionisprojectedtodecrease(figuremitigatedbyrelativelyhigheconomicgrowth,leadingto7-11,left),whichisprimarilyaresultofprojectedexpansionarelativelyconstantlowfuelwooddemandandpricelevelinfuelwoodconsumptionandlimitedincreaseinindustrialroundwoodconsumption.Theotherthreescenariosexhibitasteadyincreaseinthefinalconsumption,rangingfrom72to107millionmtacrosstheRPAscenariosby2070.Europeisundoubtedlythelargestwoodpelletconsumer(figure7-11,right),followedbyNorthAmerica.Thegrowingtrendcontinuesthroughoutthesimulationandthetotalconsumptionofwoodpelletsinthesetworegionsreaches53.2millionmtand9.6millionmtby2070,respectively(from31.4millionmtand4.8millionmtin2020,respectively).However,itisimportanttonotethatfutureFigure7-10.Projectedaveragepricesforglobalsoftwoodfuelwood(left)andhardwoodfuelwood(right)byRPAscenario,2020to2070,relativeto2015averageprices.GlobalSoftwoodFuelwoodPriceGlobalHardwoodFuelwoodPriceLMHMHLHHBaseyeardatapointLM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.7-10FutureofAmerica’sForestsandRangelandsFigure7-11.Historic(2012to2015)andprojected(2020to2070)globalwoodpelletconsumptionacrossRPAscenarios(left)andbyregionwithintheRPAHMscenario(right).ConsumptionacrossScenariosConsumptionbyRegion–HMScenarioLMHMHLAsiaEuropeAfricaOceaniaSouthAmericaNorthAmericaCentralAmericaHHHistoricLM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.woodpelletmarketshaveanadditionallayerofuncertaintyoutputshavebeengraduallyrising(Brandeisetal.2021).comparedtootherproductsgiventhestrongdependenceConsumptionwilllikelysurpasstheGFClevelin2020andonforeignpolicyandthetreatmentofwoodinrenewableisprojectedtocontinuetogrowby2070inallfourRPAenergytargets.scenarios(figure7-12,left).TheprojectedglobalroundwoodconsumptiontrendsdirectlyhingeonassumptionsaboutBetween1990and2015,theglobalsoftwoodindustrialfutureeconomicgrowth.Theconsumptionofsoftwoodroundwoodconsumptionfluctuatedgreatly,especiallyindustrialroundwoodmorethandoublesintheRPAHHduringthedeeprecessionof2007to2009(sometimesscenariobutonlyincreasesby8percentaboveits2020referredtoastheGreatFinancialCrisis,orGFC).AfterlevelintheRPAHLscenario.Regionally,thehighesttheU.S.housingbubbleburstin2008,softwoodindustrialconsumptiongrowthisfoundinAsia,withChinaandIndiaroundwoodconsumptionfellsharply.NorthAmericaandpropellingthegrowth(figure7-12,right).ItisprojectedEuropeexperiencedthemostsevereconsumptiondrop.thatindustrialroundwoodconsumptioninAsianmarketsWithnewhousingconstructionrisingsince2009,softwoodwillexceedthatoftheNorthAmericanmarketin2050lumberpriceshaverisen,andsoftwoodlumberandtimberundertheHMscenarioandreach511millionm3in2070.Figure7-12.Historic(1990to2015)andprojected(2020to2070)globalsoftwoodindustrialroundwoodconsumptionacrossRPAscenarios(left)andbyregionwithintheRPAHMscenario(right).ConsumptionacrossScenariosConsumptionbyRegion–HMScenario2,5002,0001,5001,0005000LMHMHLAsiaEuropeAfricaOceaniaSouthAmericaNorthAmericaCentralAmericaHHHistoricLM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.2020ResourcesPlanningActAssessment7-11ThelowestconsumptiongrowthoccursinCentralAmerica,Thehistoricaldataindicatethatastructuralshifthadbeenwhereeconomicdevelopmentisassumedtobeslowandtakingplaceinprintingandwritingpapermarketssincethefragmented.NorthAmericahasbeen,andisexpectedtobeginningoftheGFC.Asthedigitalagematures,demandcontinuetobe,thehighestpercapitaconsumerofsoftwoodforprintingandwritingpapersisexpectedtocontinueitsroundwoodwith798m3percapitain2020andremaintrendofconsumptiondeclinethroughouttheprojectionsaroundthislevelthrough2070.Asiaisexpectedtoincrease(figure7-14,left).InFOROM,thelevelofdigitalmaturityitspercapitaconsumptionofsoftwoodroundwoodfrom61isrepresentedbyGDPpercapita.Withtherapidgrowthm3percapitain2020to100m3percapitain2070.inrealGDPpercapita,theLMscenarioseesthelargestreductionsintheconsumptionofnewsprintandprintingSimilarly,forhardwoodindustrialroundwoodandwritingpaper,toslightlymorethanone-fourth(26.12consumption,thelargestincreaseoccursintheHHscenariopercent)ofits2020levelby2070.ThedeclineismoderateandthesmallestintheHLscenario(figure7-13,left).intheHLscenario,wherefinalconsumptionby2070Thedifferencebetweenthetwoscenariosreaches1400amountsto65percentof2020globalconsumptionlevelsmillionm3in2070.Globalhardwoodindustrialroundwood(106.68millionmtin2020).Figure7-14(right)showsaconsumptionforscenariosHMandLMfallbetweenHHconsistentnegativetrendintheconsumptionofnewsprintandHLconsumptionlevelsthroughouttheprojectionandprintingandwritingpaperacrossregionsundertheperiod,largelybecauseeconomicgrowthassumptionsHMscenario.AsiaaccountsforthelargestproportionofforthesescenariosalsofallbetweenHHandHL.Atthereduction,fallingfrom38millionmtto11millionmtbyregionallevel,Asiaisprojectedtocontinuetodominate2070,followedbyEuropeandNorthAmerica.Othershardwoodindustrialroundwoodconsumption(figure7-13,havealsohighlightedthisinverserelationshipbetweenright).Theirshareofglobalconsumptionisprojectedeconomicgrowthandpaperconsumption,whereeconomictoincreasefrom48.2percentin2020to54.7percentindevelopmentacceleratesdigitalization,andconsumption2070,reaching844.5millionm3undertheHMscenario.patternsmorerapidlyshiftawayfromhardprinttodigitalIncontrast,otherregionalmarketsonlyexperienceminoralternatives(seeJohnston2016).additionstotheirroundwooduse.SouthAmericaisthehighestpercapitaconsumerofhardwoodroundwood,consuming340and487m3percapitain2020and2070respectively.Meanwhile,Europeisprojectedtoincreaseitsconsumptionofhardwoodroundwoodfrom97to165m3percapitafrom2020to2070.Figure7-13.Historic(1990to2015)andprojected(2020to2070)globalhardwoodindustrialroundwoodconsumptionacrossRPAscenarios(left)andbyregionwithintheRPAHMscenario(right).ConsumptionacrossScenariosConsumptionbyRegion–HMScenario3,0002,5002,0001,5001,0005000LMHMHLAsiaEuropeAfricaOceaniaSouthAmericaNorthAmericaCentralAmericaHHHistoricLM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.7-12FutureofAmerica’sForestsandRangelandsFigure7-14.Historic(1990to2015)andprojected(2020to2070)globalnewsprintandprintingandwritingpaperconsumptionacrossRPAscenarios(left)andbyregionwithintheRPAHMscenario(right).ConsumptionacrossScenariosConsumptionbyRegion–HMScenarioLMHMHLAsiaEuropeAfricaOceaniaSouthAmericaNorthAmericaCentralAmericaHHHistoricLM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.U.S.TrendsandProjectionsRoundwoodProductionandPrices❖U.S.roundwoodproductionandpricesareHistoricaldataandprojectionsofU.S.roundwoodproductionbyRPAscenarioareprovidedinfigure7-15.projectedtotrendupwardacrossallscenarios,asTheproductionofroundwoodintheUnitedStatestrendedwoodproductdemandincreasesthrough2070.downwardsfromthe1990suntilthelate2000s.TheglobalMostprojectedproductiongrowthemergesfromfinancialcrisisin2007to2009sawasharpreductionintheRPASouthRegion,despiteprojectedforestroundwoodproductionintheUnitedStates,fallingfrom466areashrinkage.millionm3in2007to341millionm3by2009.Asignificantdriverofthisdeclinewasthefallinresidentialhousing❖Overseasmarketsareprojectedtosupportconstruction,whichdroppedbyabout75percentbetween2007and2009(figure7-3).Associatedwiththisdropwasincreasingnetexportsofhardwoodlumber,afallinthedemandforbuildingmaterials,particularlyandtheUnitedStatesisprojectedtobecomeaffectingsoftwoodlumberandstructuralpanelmarkets.increasinglydependentonsoftwoodlumberimports.Figure7-15.Historic(1990to2015)andprojected(2020to2070)U.S.roundwoodproductionbyRPAscenario.❖Becauseofprojectedcontinuedshrinkageinthedemandforgraphicspaperandmodestincreasesinthedemandforotherpaperproducts,pulpproductionisprojectedtoonlyincreaseslightlyoverthenext50years.TwoRPAscenarios(LMandHH)projectaneardoublinginthenetexportofnon-graphicspaperoverthisperiod.❖TheRPASoutheastandSouthCentralSubregionsareprojectedtocontinuetosupplythevastmajorityofwoodpelletswithintheUnitedStatesandremaintheprimaryU.S.sourceofpelletexportsthrough2070.LMHMHLHHHistoricLM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.2020ResourcesPlanningActAssessment7-13Sincethen,residentialhomeconstructionandindustrialFigure7-17.Historic(1990to2015)andprojected(2020to2070)U.S.roundwoodproductioncontinuetorebound,withindustrialroundwoodproductionbytypefortheRPAHMscenario.roundwoodproductionrisingbyroughly20percentbetween2009and2015.Fuelwood(softwood)Fuelwood(hardwood)ProjectionsofroundwoodproductionacrossscenariosreachOtherroundwood(softwood)Otherroundwood(hardwood)betweenanestimated467to646millionm3by2070(figureIndustrialroundwood(softwood)Industrialroundwood(hardwood)7-15).TheproductionofroundwoodisdeterminedlargelybytheevolutionofGDP,whichvariesfromlowundertheHM=highwarming-moderateU.S.growth.HLscenario,tohighundertheHHscenario.ConsumerpreferencesforfuelwoodalsoimpactthelevelofroundwoodhardwoodandsoftwoodundertheHMscenarioovertheproduction.WhiletheLMscenarioisassociatedwithonlynext50years,drivenlargelythroughtherapidconsumptionmoderategrowthinrealGDPpercapita,itreliesontheexpansionofdevelopingeconomiessuchasChinaandIndia.socioeconomicdevelopmentsunderSSP1whichisgroundedonstrongsustainabilitypreferencesfavoringbioenergySince1990,industrialroundwoodfromsoftwoodand(seefigures7-8and7-9).Consequently,theLMscenariohardwoodspeciescomposedover80percentoftotalproducesasimilarlyhighlevelofroundwood.U.S.(androundwoodproduction(figure7-17).BeforetheGFC,theglobal)projectiondataforthisassessmentareavailablefromdeclinesinroundwoodproductioncamepredominantlyJohnstonetal.(2022).fromfuelwoodandotherroundwoodcategories,whileFigure7-16showstheexportshareofindustrialroundwoodsoftwoodandhardwoodindustrialroundwoodwasmoreproductionforsoftwoodandhardwoodroundwood.Thestable.However,duringtheGFC,thelargestimpactsGDPimpactsoftheGFCwerepronouncedwithinthewereinthesoftwoodindustrialroundwoodsector,drivenUnitedStates,leadingtosharpreductionsinthedemandforthroughsharpGDPimpactsaffectingresidentialhousingandbuildingmaterials.Whilesimilareffectswerebeingfeltinothersoftwood-demandingsectors.FOROMprojectstheforeigneconomies,theytendedtobelesssevereonaverage.productionofsoftwoodindustrialroundwoodwillreturntoAsaresult,thisledtoareversalofthetrendofadecliningpre-GFClevelsinthecomingdecades,andmildgrowthinshareofsoftwoodroundwoodproductionbeingexportedhardwoodindustrialroundwoodproductionwillmaterialize,observedinthe1990sforsoftwoodroundwood,asdomesticdrivenlargelythroughincreaseddemandforhardwoodfibermarketsbegantoseekforeignbuyerstocompensatefromemergingeconomieslikeIndiaandChina.forreduceddomesticdemand.Marketsforhardwoodroundwooddependlessongrowthinresidentialhousing,TheFOROMmodelrecognizesRPAAssessmentregionsasandexportsharesofproductionremainedstablethroughtheseparateproducing,consuming,andtradingregionswithinGFCperiod.Lookingforward,FOROMprojectsanincreaseacompleteglobalmarketandcancapturemarketdynamicsintheshareofroundwoodproductionexportedforbothbyregionacrossscenarios.Figure7-18depictsroundwoodproductionprojectionsbyRPAregionandbytype,fortheFigure7-16.Historic(1990to2015)andprojected(2020to2070)U.S.HMscenario.TheclassificationofforestproductsusedinindustrialroundwoodexportsasshareofproductionfortheRPAHMthischapterisdescribedindetailinJohnstonetal.(2021,scenario.tableA-3).Mostofthegrowthacrossregionsisprojectedtocomefromincreasedproductionofindustrialroundwood,HM=highwarming-moderateU.S.growth.whileotherroundwoodandfuelwood,regardlessofspecies,isexpectedtoremainconstant.MostofthesoftwoodindustrialroundwoodproductionisprojectedtocontinuetocomeoutoftheRPASouthandPacificCoastRegions,withthelargestgrowthinsoftwoodindustrialroundwood7-14FutureofAmerica’sForestsandRangelandsFigure7-18.ProjectedroundwoodproductionbyRPAregionfortheRPAHMscenario,2020to2070.TheRPANorthandSouthRegionsarebrokenintosubregionstoprovideadditionalinformation.PacificCoastRockyMountainNorthCentralMillioncubicmetersMillioncubicmetersMillioncubicmetersNortheastSouthCentralSoutheastMillioncubicmetersMillioncubicmetersMillioncubicmetersIndustrialroundwood(hardwood)Industrialroundwood(softwood)Otherroundwood(hardwood)Otherroundwood(softwood)Fuelwood(hardwood)Fuelwood(softwood)HM=highwarming-moderateU.S.growth.2020ResourcesPlanningActAssessment7-15productioncomingoutoftheSouthCentralandSoutheastConversely,thelowergrowthHLscenarioputsminimalSubregionsdespiteprojectedlossesinforestarea(seepressureontheforestsectortomeetdemand,yielding,theForestResourcesChapter).Meanwhile,thetwoRPAonaverage,analmost-stagnantpathintheUnitedStates.northernsubregionsrelymoreonhardwoodindustrialSimilartrendsareprojectedforaverageU.S.hardwoodroundwoodproduction.Despitethis,thelargestgrowthinindustrialroundwoodprices(figure7-19,right).hardwoodproductionisprojectedtocomeoutoftheSouthCentralSubregion.SolidWoodProductsTheaveragepriceofsoftwoodindustrialroundwoodhasLumberbeenonadecliningtrendinrecentyears,whichisprojectedTheproductionoflumberintheUnitedStateshadbeenonantocontinueintheshortrun(figure7-19,left).ThistrendincreasingtrendbeforetheGFC(figure7-20,left),dominatedcouldreversequicklyunderahigh-growthfuturescenario.bytheproductionofsoftwoodlumber—representingaboutThehighestGDPscenario—theHHscenario—elicitsthe70percentoftotalannuallumberproductionduringthistime.greatestdemandforwoodproducts,increasingthepriceofindustrialroundwoodthemostrelativetotoday’slevels.Figure7-19.ProjectedaveragepricesforU.S.softwoodindustrialroundwood(left)andhardwoodindustrialroundwood(right)byRPAscenario,2020to2070,relativeto2015averageprices.SoftwoodIndustrialRoundwoodHardwoodIndustrialRoundwoodDollarspercubicmeter(2015dollars)Dollarspercubicmeter(2015dollars)LMHMHLHHBaseyeardatapointLM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.Figure7-20.Historic(1990to2015)andprojectedU.S(2020to2070):lumberproduction(left),softwoodlumbernetexports(middle),andhardwoodlumbernetexports(right),byRPAscenario.LumberProductionSoftwoodLumberNetExportsHardwoodLumberNetExportsMillioncubicmetersPercentMillioncubicmetersLMHMHLHHHistoricLM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.7-16FutureofAmerica’sForestsandRangelandsThelumbersectorexperiencedasharpreductioninproductiontrendofnetexportsofhardwoodlumberexportsfromthein2008to2009,broughtaboutthroughreduceddemandforUnitedStates,rangingfromatleast5millionm3by2070residentialhomebuildingmaterials.Duringthistime,totalundertheHLscenariotoasmuchas12millionm3by2070lumberproductionfellfrom93millionm3in2007to54undertheHHscenario(figure7-20,right).millionm3by2009.Historically,theUnitedStatesconsumedmorethanitproduced,makingitsnetexports(exportsU.S.lumberproductionisprojectedtocontinuetobeminusimports)negativeforsoftwoodlumber,sourcingdominatedbytheproductionofsoftwoodlumber,cominglumberprimarilyfromCanada.DuringtheGFC,netexportsprimarilyoutoftheRPASouthandPacificCoastRegionscontractedtowardszero(figure7-20,middle),drivenlargely(figure7-21,left).WhilethePacificCoastiscurrentlythethroughasharpreductionintheimportoflumber,asthelargestproducerofsoftwoodlumber,themodelpredictsonlydemandforthisproducterodedwithreducedresidentialhomea7-percentincreaseinproductionintheregionbetweenconstruction.Incontrast,theUnitedStateshashistorically2020and2070.Meanwhile,investmentsinplantingandbeenapositivenetexporterofhardwoodlumber(figure7-20,plantationforestshavetheSouthCentralandSoutheastright).NetexportsofU.S.hardwoodlumberwererelativelySubregionsincreasingproductionby32and36percentunaffectedbytheGFC,becausedemandforhardwoodlumberduringthisperiod,respectively.Alternatively,productionofislesssensitivetofluctuationsinresidentialconstruction,andhardwoodlumberisconcentratedinthefourRPASouthandbeinganetexporterofhardwoodlumbermeantthistradeNorthsubregions,representing95percentoftotalhardwoodpatternwaslesssensitivetothedomesticeconomicimpactsoflumberproductioncombined(figure7-21,right).GrowthintheGFC.productionofhardwoodlumberisprojectedtobedistributedapproximatelyevenlyacrossthesemajorproducingThefutureoflumberproductionintheUnitedStatesissubregions,driveninlargepartthroughincreasedforeignprojectedtobelargelydrivenbytheevolutionofGDPdemandfortheseproductsfromemergingmarkets.assumedintheRPAscenarios.Thehigh-incomeHHscenarioseesthelargestincreaseintheproductionofWood-BasedPanelslumber,risingfrom76millionm3in2015to117millionm3by2070(figure7-20,left).Meanwhile,thelow-incomeTheproductionofwood-basedpanelsintheUnitedStatesHLscenarioprojectsU.S.lumberproductiontoreachonlyexperiencedasimilaradverseeffectfromtheGFCandhad84millionm3by2070.Thescenariosprojectacontinuedyettoreturntopre-GFClevelsasof2015(figure7-22).trendofnetsoftwoodimports(negativenetexports)underThisisdue,inpart,totheslowreboundinU.S.residentialallscenarios(figure7-20,middle).Itisprojectedthathomeconstruction(figure7-3),andthecontinuedriseofnetimportsofsoftwoodlumberintheUnitedStateswillChinaasthedominantwood-basedpanelsupplier.Despiteincreaseto31millionm3by2070underthelow-incomeHLproducing35millionm3in2015,theUnitedStateshasmostscenario,andasmuchas62millionm3by2070undertherecentlybeenanetimporterofwood-basedpanels(figureHHscenario.Meanwhile,thescenariosprojectacontinued7-22),againdueinparttothelow-costalternativescomingFigure7-21.Historic(1990to2015)andprojected(2020to2070)U.S.productionofsoftwoodlumber(left)andhardwoodlumber(right)fortheRPAHMscenario.SoftwoodHardwoodMillioncubicmetersMillioncubicmetersPacificCoastRockyMountainNorthCentralNortheastSouthCentralSoutheastHistoricHM=highwarming-moderateU.S.growth.2020ResourcesPlanningActAssessment7-17Figure7-22.Historic(1990to2015)andprojected(2020to2070)U.S.wood-basedpanelsproduction(left)andnetexports(right)byRPAscenario.PanelProductionPanelNetExportsMillioncubicmetersMillioncubicmetersLMHMHLLMHMHLHHHistoricHHHistoricLM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.fromforeignmarketssuchasChina.Whileproductionofmillionm3in2070undertheHHscenario.Thecountryispanelshashistoricallybeendominatedbytheproductionofprojectedtobecomeanevenlargernetimporterofpanelsplywoodandveneer(figure7-23),theshareofproductionundertheHLscenario,asthelow-incomepathprovidesfromparticleboardandorientedstrandboard(OSB)andlessforeigndemandcompetingfortheseproducts(figurefiberboardhasbeenincreasingsincethe1990s.In2020,7-22).Conversely,theoppositeistruefortheHHscenario,about70percentoftotalwood-basedpanelproductionwherehighincomegrowtharoundtheworldcreatesmoreoriginatedintheRPASouthRegion(figure7-24).competitionforpanels,raisingpricesandpushingtheUnitedStatestoreduceitsimports.Theproductionofwood-basedpanelsintheUnitedStatesisprojectedtocontinuetoincreaseunderallscenariosProductionofpanelsisprojectedtocontinuetorelyheavily(figure7-22).Thelow-incomeHLscenariohasproductionontheSouthCentralandSoutheastSubregionsthrough2070risingfrom36millionm3in2015to40millionm3by(figure7-24).UndertheHMscenario,itisprojectedthatwhile2070.Productionisprojectedtoincreasetoashighas72plywoodandveneerproductionwillcontinuetorisemodestly,Figure7-23.Historic(1990to2015)andprojected(2020to2070)U.S.Figure7-24.Historic(1990to2015)andprojected(2020to2070)U.S.wood-wood-basedpanelsproductionbytypefortheRPAHMscenario.basedpanelsproductionbyregionfortheRPAHMscenario.MillioncubicmetersMillioncubicmetersPacificCoastRockyMountainNorthCentralNortheastSouthCentralSoutheastHistoricHM=highwarming-moderateU.S.growth;OSB=orientedstrandboard.HM=highwarming-moderateU.S.growth.7-18FutureofAmerica’sForestsandRangelandsmuchofthegrowthwillcomefromfiberboard,andtoalesserFigure7-26.Historic(1990to2015)andprojected(2020to2070)U.S.pulpextentfromparticleboardandOSB(figure7-23).In1990,productionbyregionfortheRPAHMscenario.plywoodandveneerproductioncomprised74percentofallwood-basedpanelsproductionintheUnitedStates.By2015,Millionmetrictonsthisnumberhaddeclinedto31percent.FiberboardisexpectedtoincreaseitsrelativeimportanceinU.S.panelproduction,risingfrom26percentofallproductionin1990to31percentby2070intheHMscenario.TheaggregateofparticleboardandOSBproduction,meanwhile,hasgrownfromanegligibleamountin1990tothelargestshareoftotalpanelsproductionbyvolumeby2070.PulpandPaperPacificCoastRockyMountainNorthCentralNortheastSouthCentralSoutheastHistoricPulpproductionintheUnitedStatesincreasedfrom82millionm3in1990to92millionm3by2015(figure7-25).GiventheHM=highwarming-moderateU.S.growth.projecteddeclinesinconsumptionofnewsprintandprintingandwritingpaperacrossallscenarios,itfollowsthatonly1990s.Meanwhile,wastepulphasbeenincreasingitssharemodestgrowthinpulpproductionisprojected.Forexample,oftotalpulpproductionsincethe1990s,risingfrom33U.S.pulpproductionreachesanestimated99millionm3inpercenttoabout50percentoftotalpulpproductionby20152070undertheHLscenario,whileitisprojectedtoreach(figure7-27).TheU.S.productionofpulpisprojectedto128millionm3in2070undertheHHscenario.TheSoutheastcontinuetobedominatedbywasteandchemicaltypes.andSouthCentralSubregionsdominateotherregionsinpulpproductioncurrently,representingabout78percentofallpulpThedemandforpulpisderivedthroughthedemandforoutputin2020.Itisprojectedthatmuchofthegrowthinpulpfinalpaperproducts(newsprint,printingandwritingpaper,productionwillcomefromtheSoutheast,SouthCentral,andandotherpaperandpaperboard).Asdescribedearlier(seetoalesserextent,theNorthCentralSubregionsbetween2020figure7-14),thelastdecadehasseenastructuralbreakinand2070(figure7-26).thedemandfornewsprintandprintingandwritingpaper,asconsumersswitchtowarddigitalsubstitutes.IntheUnitedMostofthepulpproducedintheUnitedStatesiswaste(i.e.,pulpmadefromrecycledpaper)andchemicalforms.MechanicalpulphashistoricallyrepresentedasmallshareoftotalproductionandhasbeendecreasingfurthersincetheFigure7-25.Historic(1990to2015)andprojected(2020to2070)U.S.pulpFigure7-27.Historic(1990to2015)andprojected(2020to2070)U.S.pulpproductionbyRPAscenario.productionbytypefortheRPAHMscenario.MillionmetrictonsMillionmetrictonsLMHMHLMechanicalpulpChemicalpulpOtherwoodpulpWastepulpHM=highwarming-moderateU.S.growth.HHHistoricLM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.2020ResourcesPlanningActAssessment7-19States,theconsumptionoftheseproductspeakedintheearlyThesensitivityofthesesectorstothepathofGDPis2000sandhassincebeenonasteadydecline(figure7-28).highlightedinfigures7-29and7-30showingdivergingMeanwhile,thedemandforotherpaperandpaperboardhaspatterns.Fornewsprintandprintingandwritingpaper,lowbeenrelativelystableintheUnitedStatesduringthistime,economicgrowthintheHLscenarioyieldsaslowerpathofdriveninlargepartbyincreaseddemandforpackagingdigitalization,andthereforeaslowerpathforsubstitutingmaterialstosupportonlineshoppingandtherobustdemandawayfromthesepaperproducts(figure7-29).Asaresult,fortissuepapers,whichriseswithGDP.Consumptionofitisprojectedthatproductionofthecombinednewsprintnewsprintandprintingandwritingpaperwere75and38andprintingandwritingpaperproductswillbe63percentpercentbelowtheir2000levelsby2015,respectively.Thebelow2000levelsby2070underthelow-incomeHLconsumptionlevelsforotherpaperandpaperboardwerescenario,andasmuchas77percentbelow2000levelsunderrelativelyunaffectedduringthisperioddespitetheimpactsoftheGFC.Itisprojectedthatnewsprint,andprintingFigure7-29.Historic(1990to2015)andprojected(2020to2070)U.S.andwritingpaper,willcontinuethistrendthrough2070,productionofnewsprintandprintingandwritingpaperbyRPAscenario.decliningto94and65percentbelowtheir2000levelsby2070,respectively,undertheHMscenario.Otherpaperandpaperboardisprojectedtocontinuestablegrowth,growing9percentaboveits2000levelsby2070,undertheHMscenario.Figure7-28.Historic(1990to2015)andprojected(2020to2070)U.S.paperMillionmetrictonsconsumptionbytypefortheRPAHMscenario.MillionmetrictonsLMHMHLHHHistoricLM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.Figure7-30.Historic(1990to2015)andprojected(2020to2070)U.S.productionofotherpaperandpaperboardbyRPAscenario.NewsprintOtherpaperandpaperboardPrintingandwritingpaperHM=highwarming-moderateU.S.growth.MillionmetrictonsLMHMHLHHHistoricLM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.7-20FutureofAmerica’sForestsandRangelandsthehigherincomeHHscenario.Conversely,otherpaperFigure7-32.Historic(1990to2015)andprojected(2020to2070)U.S.netandpaperboardproduction—whichiscomplementarytoexportsofotherpaperandpaperboardbyRPAscenario.digitalizationasitsupportspackagingforonlineordershipments—yieldsasmuchasa28-percentincreaseoverMillionmetrictons2000levelsby2070underthehigh-incomeHHscenario.TheHLscenarioyieldsamere8percentgrowthinU.S.LMHMHLHHHistoricproductionofotherpaperandpaperboardfrom2000levelsby2070,becauseloweconomicgrowthisrelatedtolowerLM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highmanufacturinggrowthandconnectedtoaslowerrateofwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.growthinonlinepurchasesandthepackagingneededfordeliveriestoconsumers.acombined77percentoftotalU.S.productionin2020.UndertheHMscenario,itisprojectedthattheseTheU.S.hashistoricallybeenanetimporterofnewsprintsubregionswillloseabout50percentoftheirproductionandotherprintingandpaperproducts(figure7-31).Theofnewsprintby2070(figure7-33).Yet,thisislowerthantrendofdecreasingdemandfortheseproducts,aswellastheproportionalimpactinsomeotherU.S.regions.WhiletheeconomicimpactsassociatedwiththeGFC,cutnetthePacificCoastisaminorplayerintheproductionofimportstonearly1/3relativetopre-GFClevels.Thistrendisnewsprint,itisexpectedthisregionwillloseabout84expectedtocontinueastheU.S.andothereconomiescontinuepercentofitsproductionduringthesameperiod.todigitalizeandisrelativelyinsensitivetothedegreeofeconomicgrowthunderthevariousscenarios.OntheotherFigure7-33.Historic(1990to2015)andprojected(2020to2070)U.S.hand,theUnitedStateshashistoricallybeenanetexporterofproductionofnewsprintandprintingandwritingpaperbyregionfortheRPAotherpaperandpaperboardproducts(figure7-32),broughtHMscenario.onbythemovetowardsonlineshopping.Exportsoftheseproductsaresensitivetoassumptionsaboutfutureeconomicgrowth,asthedemandforshippingmaterialsdependslargelyonthedevelopmentofemergingmarketslikeIndiaandChina.ItisprojectedthatexportsofU.S.otherpaperandpaperboardproductswillremainstagnantorevendeclineslightlyundertheHLscenarioyetcontinuetoincreasesharplyunderthehigherincomeHHscenario.ProductionofnewsprintisconcentratedwithintheSoutheastandSouthCentralSubregions,representingFigure7-31.Historic(1990to2015)andprojected(2020to2070)U.S.netexportsofnewsprintandprintingandwritingpaperbyRPAscenario.MillionmetrictonsPacificCoastRockyMountainNorthCentralNortheastMillioncubicmetersSouthCentralSoutheastHistoricHM=highwarming-moderateU.S.growth.LMHMHLHHHistoricLM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.2020ResourcesPlanningActAssessment7-21TheU.S.productionofotherpaperandpaperboardundertheWoodEnergyHMscenarioisprovidedinfigure7-34,whereproductionisconcentratedagainintheSouth,andtoalesserdegreeTheproductionoffuelwoodwithintheUnitedStateshasintheNorth.Growthintheproductionoftheseproductsisbeenrelativelyconstantoverthelastcoupledecades,afteraprojectedtobeconcentratedintheSouth,withtheSoutheastperiodofsignificantdeclines(figure7-35,left).Asof2015,andSouthCentralgrowingnearly25and10percenttheU.S.producedabout44millionm3offuelwood.Therespectivelyfrom2020to2070.OtherregionsexperienceRPAscenariosprojectmodestvariationintheproductionofmoremodestgainsofbelow10percent.fuelwoodthrough2070.Lookingatthetwomostextremepathways,thelowestlevelsarereachedunderthehighFigure7-34.Historic(1990to2015)andprojected(2020to2070)U.S.economicgrowthHHscenario(34millionm3by2070),productionofotherpaperandpaperboardbyregionfortheRPAHMscenario.whilethesustainablymindedLMscenarioyieldsthehighestlevels(65millionm3by2070).MillioncubicmetersTheproductionoffuelwoodisdistributedacrossthefourPacificCoastRockyMountainNorthCentralNortheastRPAregions,withtheSouthCentralSubregioncontributingSouthCentralSoutheastHistoricthelargestshare(figure7-35,right).FOROMestimatesthat31percentoffuelwoodwasproducedintheSouthCentralHM=highwarming-moderateU.S.growth.in2020,followedby21percentinboththeSoutheastandNorthCentral.ThesesharesdonotchangemarkedlythroughouttheHMscenarioprojection.Thisassessmenttreatswoodpelletsasauniqueproduct,independentfromfuelwood,yetwoodpelletsmayuseindustrialroundwood,fuelwood,and/orwoodprocessingresidualsasfeedstock.Thisrelationshipiscalibratedattheregionalleveltorecentreportedfeedstockutilizationoutlinedinthe2013UNECE/FAOJointWoodEnergyEnquiry.Asmentionedintheglobalsection,thewoodFigure7-35.Historic(1990to2015)andprojected(2020to2070)U.S.fuelwoodproductionbyRPAscenario(left)andbyregionfortheRPAHMscenario(right).ProductionbyScenarioProductionbyRegion–HMScenarioMillioncubicmetersMillioncubicmetersLMHMHLPacificCoastRockyMountainNorthCentralNortheastSouthCentralSoutheastHistoricHHHistoricLM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.7-22FutureofAmerica’sForestsandRangelandspelletmarkethasexperiencedsignificantgrowthinand,ultimately,aprojectionthatwoodpelletconsumptionthelastnumberofyears,withEuropeemergingastheincreasestoover20millionmtby2070,representingclosedominantconsumer,relyingsignificantlyontheimportofto4.2percentoftotalannualremovals.woodpelletsfromtheU.S.Accordingly,theproductionofwoodpelletsintheUnitedStateshasalsoexhibitedWithintheUnitedStates,woodpelletproductionhasbeenstronggrowthinrecentyears,reachingnearly9millionoverwhelminglyfocusedintheSouth(figure7-36,right).mtby2020.ProjectionsarehighlysensitivetotheRPAIn2020,itisestimatedthat65percentofallwoodpelletsscenarioandtheunderlyingSSPrelatedassumptionsproducedinthecountrywereproducedintheSoutheast,onpreferencesandpolicies(figure7-36,left).TheHLfollowedby33percentintheSouthCentralSubregion.scenarioisalow-growthscenario,wherelittlepreferenceUndertheHMscenario,bothsubregionscontinuetoisgiventosustainabilitygoalstopromotetheuseofwoodproducethevastmajorityofwoodpellets,withthehighestpelletsinenergyproduction.Accordingly,U.S.pelletgrowthratesobservedintheSouthCentralSubregion.productionplateausaroundcurrentlevelsbeforeshiftingPartoftheSouth’scontinueddominanceinwoodpellettoadecliningtrend,reachingabout4millionmtby2070.productionrelatesnotonlytoitshighquantityofavailableAlternatively,themoresustainability-orientedLMscenariotimber,butalsoitsrelativeproximityasatradingpartnerassumeshighgrowthinwoodpelletsaroundtheworld,tosupplytheEU’scontinueddemandfortheproductasaleadingtocontinuedgrowthinU.S.productionforexportcarbon-beneficialsourceofenergy.Figure7-36.Historic(1990to2015)andprojected(2020to2070)U.S.woodpelletproductionbyRPAscenario(left)andbyregionfortheRPAHMscenario(right).ProductionbyScenarioProductionbyRegion–HMScenarioMillionmetrictonsMillionmetrictonsLMHMHLPacificCoastRockyMountainNorthCentralNortheastSouthCentralSoutheastHistoricHHHistoricLM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.2020ResourcesPlanningActAssessment7-23ManagementImplicationslikelytocontinue,implyingsteadydisinvestmentingraphicspapermanufacturingcapacity.OtherpaperandpaperboardGlobalproductionofbothhardwoodandsoftwoodroundwoodconsumption,incontrast,generallyincreasesacrossallareprojectedtoriseintothefuture,andthescenarioswescenarios.TheUnitedStatesisprojectedtoeithermaintainitsreportsupporttheideathatthesemarketswouldbemaintainedpositivenetexportstatus(HLandHMscenarios)orincreaseinthecoming5decades.ForhardwoodintheUnitedStates,itsnetexports(LMandHHscenarios)inotherpaperandastrongoverseasmarketforroundwoodandlumberimplypaperboard.TheSouthCentralandSoutheastareprojectedtolikelysteadytogrowingopportunitiesforexports.Suchcontinuetodominatedomesticpaperproduction,highlightingstrengthinhardwoodmarketstranslatesintogenerallylikelygeographicregionswheresteadytohigheroutputofthatunchangedtorisingpricesinbothhardwoodroundwoodandaggregatecategoryofpaperwouldbeexpected.hardwoodlumber.Incontrast,theUnitedStateshaslongbeenanetimporterofsoftwoodlumberandwood-basedpanels,Forfuelwood,thefuturedependsheavilyonincomegrowth,andmostoftheprojectedgrowthinU.S.softwoodroundwoodandconsumptioncouldriseorfallto2070.Forwoodpellets,isusedtoproducelumber,softwoodplywood,andOSBontheotherhand,onlyundertheHLscenarioisproductionfordomesticconsumption.However,growthinroundwoodprojectedtodeclineafter2030,whileoutputrisesbythreeproductionisprojectedtoexceedgrowthindomestictofivetimesby2070undertheHM,HH,andLMscenarios.consumptionacrossmostscenarios,thedifferenceaddingtoNearlyallproductionofwoodpelletsisexpectedtocomeU.S.netexports.ManagerscouldthereforeexpectgrowingfromtheU.S.South.Prospectsfordomesticproductionandopportunitiesforexports.Fromthisoutlook,managersmightexportofwoodpelletsdependsinlargepartonstrongoverseasexpectmarketstobemaintainedorstrengthenedacrossthemarkets,however,whichcurrentlyarelargelymaintainedbyUnitedStateswheremarketscurrentlyexist.EuropeanUnionpoliciesfosteringtheirconsumption.AlthoughU.S.lumberproductionisprojectedtoriseto2070,Conclusionsprojectionsalsoindicateagrowingdependenceonsoftwoodlumbernetimportsandrisinghardwoodlumbernetexports.TheU.S.forestsectorhasundergonewideswingsinBothresultshighlightthelikelysteadytostrengtheningproductionandconsumption,duetowidelyvaryingratesofmarketsforbothkindsoflumber.Producersandconsumersofeconomicgrowthovertimeandtoseculartrendsindemand.lumberwouldthereforeexpectrisingprices,onaverage,intheHigheconomicgrowthcorrespondswithincreasedresidentialcomingdecades.ScenariosalsoshowthattheSoutheastandconstructionandhigherdemandforwood-basedbuildingSouthCentralSubregions.wouldexperiencethemostrobustproducts,suchassoftwoodlumberandwood-basedstructuralgrowthinsoftwoodlumberproduction,withthePacificCoastpanels.Therefore,vigorouseconomicgrowthraisesindustrialRegionnotincreasingsignificantly.Growthinhardwoodroundwoodproduction,particularlysoftwood.Suchvigorouslumberproductionismorebroad-based,acrossallregionsofgrowth,however,alsodrivesdemandsforimports,withthethecountry.UnitedStatesremaininganetimporterofsoftwoodlumberandstructuralpanels.Incontrast,hardwoodtimberharvestsAlthoughwood-basedpanel(plywood,OSB,fiberboard)areconnectedtonotonlyU.S.economicgrowthbutalsoproductionisprojectedtoincreasethroughouttheprojectiontooverseaseconomicgrowthandinvestmentinfurnitureundermostscenarios,theNationisprojectedtomaintainmanufacturing.Overseasdemandforhardwoodroundwooditsimport-dependence.LoweconomicgrowthleadstoandlumberprovidesabaseofsupportfordomesticmorenegativenetexportsundertheHLscenario,whileproduction.AllscenariosprojectstableexportmarketsforhighgrowthleadstolessnegativenetexportsundertheHHhardwoodindustrialroundwoodandlumber.scenario.Fiberboardproductionisprojectedtoexperiencevigorousproductiongrowthto2070undertheHMscenario,TheU.S.papersectorhasundergoneatransitioninthelastanindicationoftheeffectsofsustainedU.S.economic20yearsthatisprojectedtocontinueintotheforeseeablegrowthandexportdemand.future.Inallscenarios,newsprintproductionandconsumptiondeclinetohistoricallylowlevelsby2070,whileprintingandPulpproductionisexpectedtoremaineitherunchangedwritingpaperalsodeclines,butataslowerrate.Suchdeclinesortogrow,dependingonthescenarios,andtheSouthtranslateintolowertotalquantitiesoftheirimportssincetheCentralandSoutheastSubregionsareprojectedtocontinueUnitedStatesisanetimporterofbothcategories.Thefuturetodominatethemarket.However,continuingalong-runoftheremainingpartofthepapersector,embodiedinthetrend,consumptionofnewsprintandprintingandwritingaggregatecategoryof“otherpaperandpaperboard,”however,paperisprojectedtodeclineforbothproducts,acrossallistiedmorecloselytoeconomicgrowthandrisingoverallscenarios:intheHMscenario,newsprintdeclinestonearglobaldemandforpaperforpackagingandotherhumanzeroby2040,whileprintingandwritingpaperdropsbyhalfneeds.U.S.andglobalconsumersareprojectedtocontinueby2070,comparedto2015levels.Alessonforinvestorsistodemandthosecategoriesofpaperforpackagingandforthatthetrendsobservedinconsumptionsincethe1990saresanitarypurposes.7-24FutureofAmerica’sForestsandRangelandsProjectedfuturesintheproductionandconsumptionofwoodBuongiorno,J.2021.GFPMX:acobwebmodeloftheglobalforesttogenerateenergyvarywidelybyscenario,adheringtothesector,withanapplicationtotheImpactoftheCOVID-19pandemic.storylinesembodiedintheRPAscenarios.AfutureinwhichSustainability.13(10):5507.https://doi.org/10.3390/su13105507.theUnitedStatesandtheworldusewoodtomanufacturewoodpelletsforenergyunderasustainability-orientedLMU.S.CongressionalBudgetOffice(CBO).2020.AnupdatescenarioleadstohighgrowthinwoodpelletdemandandU.S.totheeconomicoutlook:2020to2030.https://www.cbo.gov/exports.Nevertheless,woodpelletmanufactureconsumespublication/56442.(1September2021).lessthan2percentofallroundwoodconsumptiontodayandwouldnotrisetomuchmorethan4.2percentby2070underFAOStat.2021.ForestryProductionandTrade.FoodandLMandremainlessthan1percentunderHL.ConcernsaboutAgriculturalOrganizationoftheUnitedNations.http://www.fao.org/thesustainabilityandcarbonimplicationsofwoodpelletsasfaostat/en/#data/FO.(13July2021).anenergysourcewouldthereforebemostpronouncedundertheLMandleastundertheHLscenarios,butinbothcasesGordon,RobertJ.2016.TheriseandfallofAmericangrowth:Thewouldnotdefinesubstantialchangesinoverallproduction/U.S.standardoflivingsincetheCivilWar.Princeton,NJ:Princetoncarbonatthesectorlevel.UniversityPress.784p.TheroleofglobalmarketsisundeniableintheprojectionsGrushecky,S.T.;Buehlmann,U.;Schuler,A.;Luppold,W.;Cesa,madenotonlyforwoodpelletsbutalsoforallotherproducts,E.2006.DeclineintheU.S.furnitureindustry:acasestudyoftheastheUnitedStatesisamongthetopnationalproducersandimpactstothehardwoodlumbersupplychain.WoodandFiberconsumersofmostbroadcategoriesofforestproducts.ItisScience.2:365–376.forthatreasonthatU.S.projectionsaremadeinthecontextofaglobalmarketmodel.Atthesametime,theglobalmarketHetemäki,L.;Hurmekoski,E.2014.Forestproductsmarketmodelusedhereallowsfordetailedanalysisoftherelativeoutlook.InHetemäki,L.;Lindner,M.;Mavsar,R.;Korhonen,M.rolesoftheregionswithintheUnitedStates.Providingsucheds.FutureoftheEuropeanforest-basedsector:structuralchangesregionaldetailinthemarketmodelallowsforthefulleffectstowardsbioeconomy.WhatScienceCanTellUs6.Joensuu,Finland:ofglobalphenomenatobeaccountedforinregionalmarketsEuropeanForestInstitute:15–32.andintheprojectedfutureofforestconditions.TheregionaldetailadditionallyoffersinsightsonhowregionsareprojectedIntergovernmentalPanelonClimateChange[IPCC].2014.Climatetoindividuallycontributetoglobalmarketsandwhethertheirchange2014:synthesisreport.Pachauri,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onhain2018,representinga-5,928(-3.5)lossof38percent.ha=hectares.MostoftherangelandareaintheconterminousUnitedStatesSource:USDANRCS2018.existswestofthe97thmeridian(ReevesandMitchell2011).AlthoughnotpartoftheconterminousUnitedStatesandpurchasedby,non-Federalownership.Forexample,theU.S.notdiscussedinthisreport,rangelandsalsooccurinAlaska,BureauofLandManagement(BLM)hadanetdisposalofHawaii,andseveraloftheU.S.protectoratesandterritories.56,376hafromall50Statesin2020,approximately0.00057ThecompositionanddistributionofrangelandsaredescribedpercentoftheBLMlandbase(BLM2020).Similarly,inReevesandMitchell(2011,2012),whilerangelandthe2020U.S.DepartmentofAgriculture(USDA),ForesttransitionstoandfromotherlandusesaredescribedintheServicelandbasewas67,275halargerthantheaverageareaLandResourcesChapterofthisAssessment.Highlightsfromfrom2013to2019(94,093,141ha),anincreaseof0.00072thosesourcesareprovidedhere,aswellassignificanttrendspercent(USDAForestService2020).Theseexamplesinrangelandareasince2010.supportthevalidityofthestationarityassumptionfromanationalperspective.Non-FederalrangelandslostaboutTheNationalResourcesInventory(NRI),administered168,571haperyearfrom2010to2017foratotallossofbytheU.S.DepartmentofAgriculture,NaturalResourcesabout1.7millionha.GiventhatFederalrangelandareaConservationService(USDANRCS),estimated169millionremainsessentiallyconstantovertimeandthatReeveshaofnon-Federalrangelandsin1982(USDANRCS2018).andMitchell(2011)estimatedatotalrangelandareainBy2017,theestimatedareaofnon-FederalrangelandswastheconterminousUnitedStatesofabout268millionha,it163millionha,representingalossof6millionhaor3.6followsthatthetotalrangelandareaintheconterminouspercentofthenon-Federalrangelandbase(168,571haaverageUnitedStatesin2017wasabout266.3millionha.lossperyearfrom1982to2017).Morethanhalfofthenetlossinrangelandarea(3.6millionha,2.1percent)occurredTable8-2showstheproportionalownershipofrangelandsbetween1982and1992.ThedeclineinrangelandareawasacrosstheconterminousUnitedStates.Privaterangelandsdrivenbynetmovementof2.3millionhatodevelopedusescoveralargerareathanallotherrangelandownerships(urbanandruraltransportationinfrastructure)and1.2millioncombined.Ofthenon-privaterangelands,theBLMmanageshatocropland.Smallernetlosseswereobservedinshiftstoforestandotherrurallandincludingfarmsteads.Table8-2.ApproximateproportionofrangelandundermanagementintheconterminousUnitedStates.TheRockyMountainRegionhasthemostnon-FederalrangelandareaintheUnitedStates(about106millionhaOwnershipProportionProportionofin2017),followedbytheSouth,PacificCoast,andNorthofallpubliclyownedRegions(table8-1).WhileallregionslostrangelandsfromU.S.BureauofLand1982to2017,theRockyMountainRegionlostthegreatestManagementrangelandrangelandtotalamountofrangelandandtheNorthRegionlosttheU.S.DepartmentofDefensepercentpercenthighestpercentageofrangelandoverthisperiod.MissouriU.S.NationalParkServiceistheonlyStateintheNorthRegionforwhichtheNRIhasPrivatelyowned2147recordedrangelanddata,andithaslost39percentofitsStategovernmentrangelandbasesince1982.Inallregions,thelargestrangelandTribal25conversionsweretransitionstocropandurbanlandcover.U.S.FishandWildlifeService24USDAForestService550Federallymanagedrangelandsgenerallydonotundergoland613usetransitionsandarethereforeassumedtostayconstant.512Therareexceptioniswhenpubliclandsaretransferredto,or128178-2FutureofAmerica’sForestsandRangelandsthelargestproportion(47percent)whiletheU.S.FishandCRPareabyRPARegionAllCRPareamillionhain1993),andPacificCoastRegion(920,000hainWildlifeService(FWS)managesthesmallestproportion(Hundredsofthousandsofha)(Hundredsofthousandsofha)2007)(figure8-1).TheamountofCRPlandhasdecreased(about2percent).TheproportionofU.S.rangelandssteadilysince2007inallregions,andin2018theRockymanagedbyStategovernmentsisabout6percent.MountainRegionexhibited41percentlessCRPlandthanin2007.ThePacificCoastRegionhasexhibitedlossesofaboutTheCRP,administeredbytheU.S.Departmentof24percentsince2007,whiletheSouthandNorthRegionsAgriculture,FarmServiceAgency,hasimpactsonhavelost32and28percent,respectively,since2007.rangelandsandrangelandsustainability.CRPlandsarenotconsideredrangelandintheNRIbecausethecoverisnotRangelandConditionandHealth“permanent”;however,CRPlandsplantedtograsses,forbs,orshrubsmayprovidesimilarecologicalfunctionsand❖Relativelyhealthyconditionswerefoundonacttodecreasefragmentationinlandscapesdominatedbyrangelandvegetation.Theselandscanprovideconnectivityapproximately75percentofnon-Federalbetweendisjunctivepatchesofrangelandsthatareoftenrangelandfrom2011to2015andbetween79tofragmentedbyagriculturalorurbanlanduses(Reeveset86percentofBLMrangelandsfrom2011to2018.al.2018,Augustineetal.2021)andprovidebenefitsfromRelativelyhealthyisdefinedasless-than-moderatereducederosionandwildlifeviewingandhunting(Sullivandeparturefromreferenceconditionsforallthreeetal.2004).Inaddition,CRPlandsgenerallyimproverangelandhealthattributes—soilandsitestability,ecologicalconditionwhencomparedwithagriculturalhydrologicfunction,andbioticintegrity.landuses.EnrollmentinCRPhasledtoenhancedsoilproductivity,increasedprovisionofwildlifehabitat,and❖Invasivespeciesarehavingarelativelylargerimprovedwaterquality,allofwhicharealsotraitsofhealthyrangelands.Moreover,CRPlandshavethepotentialimpactonrangelandhealththanotherfactors.tosequesterasignificantquantityofatmosphericcarbondioxide(Yangetal.2019).ParticipationintheCRPhas❖ThisinauguralRPAevaluationofvegetationtrendsalsoledtounintendednegativeconsequences(BakkerandHiggins2009).Forexample,millionsofhectaresenrolledinacrossalllandsusingremotesensingcorroboratestheCRPareseededwithnonnativespecies,suchascrestedfindingsfromboththeNRIandtheAssessmentwheatgrass(Agropyroncristatum),intermediatewheatgrassInventoryandMonitoring(AIM)processes.(Thinopyrumintermedium),andsmoothbrome(Bromusinermus).CRPareareachedanationalpeakin2007ofabout❖ThenorthernGreatPlainsexhibitedthelargest14.7millionhafollowedbyasteadydeclineto9.1millionhain2018,representingalossof38percent(figure8-1).increasesinperennialherbaceouscoverwhileRegionally,theRockyMountainRegionhadthemostCRPtheInteriorWestandCaliforniaexhibitedtheland(peakingat7.5millionhain2007),followedbythelargestdeclines.AnnualgrassesandforbsareSouthRegion(3.7millionhain1993),NorthRegion(3.5increasingalmostuniversallyacrossrangelands,withthelargestincreasesobservedinWashington,Figure8-1.AreaofCRPundercontractfrom1986to2018fortheRPAOregon,northernNevada,andsouthernIdaho.regionsandtheconterminousUnitedStates.❖AnnualnetprimaryproductivityhasbeengenerallyYearCONUS=conterminousUnitedStates;CRP=ConservationReserveProgram;ha=hectares.increasingintheNorthwhiledecreasingintheSource:https://www.fsa.usda.gov/programs-and-services/conservation-programs/reports-and-statistics/South,especiallythedesertSouthwest,whileconservation-reserve-program-statistics/index(20May2021).interannualvariabilityhasbeenincreasingalmostuniversallysince2000.Droughteventssince2000havecreatedcontinuallylowerproductioninCalifornia,NewMexico,andArizona.❖Baregroundisdecreasinginmanyareasduetotheincreasingtrendofannualherbaceousspecies.TheexceptionisthedesertSouthwest,particularlyNewMexicoandwestTexas,whichhasexperiencedincreasedbaregroundattributabletoreducedannualnetprimaryproductivitysince2000.Rangelandhealthassessmentsprovideinformationonthefunctionofecologicalprocessesrelativetoecologicalpotential.TheprocessmostcommonlyusedtoevaluaterangelandhealthintheUnitedStatesconsiders17indicatorsrelatingtotheattributesofbioticintegrity,hydrologicfunction,andsoilandsitestability(Pellantetal.2020,2020ResourcesPlanningActAssessment8-3USDANRCS2018).TheNRIusestherangelandhealthexhibitedthebesthealthforthesoilandsitestabilityassessmentprocesstoregularlymonitorrangelandhealthattribute,with87.3percentexhibitingnone-to-slightoronnon-Federallands,althoughinferencesfromthisslight-to-moderatedeparturefromreferenceconditionsmonitoringareonlyapplicablefornon-Federallandsandandonly3.2percentexhibitingmoderate-to-extremeorforrelativelylargeareas(i.e.,biggerthanmostcounties).extreme-to-totaldeparture.Conversely,rangelandsdepartedOnFederallands,theBLMregularlycollectsdataonmostsignificantlyfromreferenceconditionsfortherangelandhealthattributesandvegetationcompositionbioticintegrityindicator,with77.3percentofrangelandsandstructureaspartoftheAIMProgram(Toevsetal.exhibitingnone-to-slightorslight-to-moderatedeparture2011a,2011b).TheAIMsamplingeffortreportsontheand5.8percentexhibitingmoderate-to-extremeorextreme-status,condition,andtrendofrangelandresourcesin13to-totaldeparture(table8-3).ThebioticintegrityindicatorWesternStatesbyannuallysurveyingthousandsofrandomfactorsinthepresenceofnonnativespecies,explaininginlocationsacrossBLMlands(Yuetal.2020).TheUSDApartwhythiselementofrangelandhealthdepartsthemostForestServicedoesnotcollectallofthedatanecessaryfromreferenceconditions(table8-3).forrangelandhealthassessment(i.e.,bioticintegrity,hydrologicfunction,andsoilandsitestability),butdoesBetween77and87percentofnon-FederalrangelandincollectdataonvegetationcompositionandstructurefromtheconterminousUnitedStateswasinrelativelyhealthynonforestlandsusingForestInventoryandAnalysis(FIA)conditionfrom2011to2015,dependingontheattributeprotocolsthroughtheAllConditionsInventory(ACI)beingexamined.Theremaining12to23percentofnon-project(Bush2012).ThecapacitytoquantifyrangelandFederalrangelandshowedmoderateorgreaterdeparturesconditionsandtrendsacrosslargeareashassignificantlyfromreferenceconditionsforatleastoneoftherangelandincreasedsincethelastRPArangelandassessmenthealthattributes,while10.5percentshowedmoderateorduetotheadditionoftheAIMprogram(theNRIhasgreaterdeparturesforallthreerangelandhealthattributesbeencollectingdatasince1982)andincreasedremote(figure8-2).Forallthreerangelandhealthattributes,thesensinganalyticalcapabilities(Reevesetal.2014b).extentofdeparturefromreferenceconditionvariedwidelyWhileremotelysensedindicatorsofrangelandtrendsacrossWesternStates.RelativelylargedeparturesforallcanenhanceourunderstandingofrangelandconditionthreeattributeswerefoundinTexas,Oklahoma,easternandhealth,theyarenotnecessarilydirectlycomparableColorado,westernKansas,andeasternWashingtonandtothegroundsamplingeffortsdocumentedinthisreportOregon,alongwithsmallerareasinotherplacessuchasgivensamplesizeissues,spatialautocorrelation,andothernorthernUtahandsouthernIdaho.considerations.ProlongedperiodsofsevereorextremedroughtNon-FederalLandsencompassedportionsofArizona,NewMexico,southeastColorado,northwestTexas,westernOklahoma,andRangelandHealthsouthwestKansasfrom2011to2015.TheseareasalsoexperiencedatleastmoderatedeparturesfromreferenceOurexaminationofnon-Federalrangelandhealthwasbasedconditionsforeachrangelandhealthattributeduringthisonthe2018NRIRangelandResourceAssessment(USDAsametimeperiod,suggestingthatextendeddroughtsmayNRCS2018),wherethedatacollectedfor17rangelandimpactrangelandhealth(figure8-2).healthindicatorsatindividualsamplelocations,assessedbasedonguidancebyPellantetal.(2005),wereaggregatedTable8-3.Proportionofnon-Federalrangelands(2011to2015)indifferenttoabroaderspatialscale(MajorLandResourceArea).categoriesofdeparturefromreferenceconditionsforrangelandhealth.EachindicatorwasassignedadegreeofdeparturebasedontheextenttowhichtheindicatorfelloutsidetherangeAttributeNone-slight,ModerateModerate-extreme,ofnaturalvariabilityforasite:none-to-slight,slight-to-slight-moderateextreme-totalmoderate,moderate,moderate-to-extreme,extreme-to-Soil/sitetotal.Thesmallerthedegreeofdeparture,the“healthier”stabilitypercentofrangelandareaathesite.Thedatacollectedduringthe2011to2015timeHydrologic(marginoferror)periodwerecomparedagainsta2004to2010referencefunctionperiod;trendanalysisisnotpossibleuntilmultipledataBiotic87.3(1.0)9.5(0.9)3.2(0.5)pointscanbecomparedagainstthereferenceperiod.Whenintegrityconsideringrangelandhealthattributesindividually,alarge84.0(1.2)12.2(1.1)3.8(0.5)majorityofnon-FederalrangelandintheWesternUnitedStatesshowedrelativelyminordeparturesfromreference77.3(1.4)16.9(1.2)5.8(0.6)conditionsduringthe2011to2015period.RangelandsaRangelandwithnodata(5.5percent)isexcluded.Source:USDANRCS2018.8-4FutureofAmerica’sForestsandRangelandsFigure8-2.Areaofnon-Federalrangelandwhererangelandhealthattributesexhibitmoderateorlargerdeparturesfromreferenceconditionfrom2011to2015:(left)locationswhereatleastoneattributeexhibitsmoderatedepartures(25.8±1.4percent),(middle)locationswhereallthreeattributesexhibitmoderatedepartures(10.5±0.9percent),and(right)locationswhereallthreeattributesexhibitabovemoderatedepartures(2.0±0.3percent).ThecoloredportionsofthemapsrepresentMajorLandResourceAreaswheresufficientnon-FederalrangelandwassampledbytheNationalResourcesInventorytoestimatetherangelandhealthparameters.Source:USDANRCS2018.InvasiveSpeciesFigure8-3.Percentofnon-Federalrangelandareawhereinvasivespecieswerepresentbetween2011to2015.ThecoloredportionsofthemapsInvasiveplantspeciesonrangelandsarenonnativeplantrepresentMajorLandResourceAreaswheresufficientnon-Federalrangelandspeciesthatareharmfultorangelands.NonnativespecieswassampledbytheNationalResourcesInventorytoestimatetherangelandareintroducedfromothercountriesorwerenativetothehealthparameters.UnitedStatesbuthistoricallyabsentfrom(oronlyminorcomponentsof)rangelandplantcommunities.NoteverySource:USDANRCS2018.nonnativespeciesisconsideredinvasive;mostnonnativespeciesdonotposeasignificantproblem,andsomeareconsideredbeneficial.Forexample,crestedwheatgrassiscommonlyrecommendedandintroducedontorangelandsinsemiaridregionsforforageproductionandsoilstabilizationeventhoughitspresencecanaffectsomespeciescomposition-relatedmeasuresofrangelandhealthinthebioticintegritycategory.Weexaminedspecificgroupsofinvasivegrasses,forbs,andwoodyplantspeciesselectedbecauseoftheirprevalenceinrangelandplantcommunities.WeprovideacursoryoverviewofdominantthemesandoffersomespecificexamplesofproblematicinvasivespeciesinfluencingrelativelylargeareasofU.S.rangelands.Acomprehensiveevaluationdescribingdozensofinvasivespeciesonnon-Federalrangelandsisprovidedinthe2018NRIRangelandResourceAssessment(USDANRCS2018).InvasivespeciesoccupyeveryStateintherangelanddomain(figure8-3).WiththeexceptionoftheSouthwesternUnitedStates,invasivespeciesarefoundon30percentormoreofthenon-Federalrangelands.Invasiveannualbromegrassesareparticularlyabundantinshrubcommunitieslikesagebrushandpinyon-juniperandoftenoutcompetenative2020ResourcesPlanningActAssessment8-5grassesandforbs.InvasiveannualbromeswerepresentonFigure8-4.Percentofnon-Federalrangelandareawhereannualbromes30(±1.4)percentofnon-Federalrangelandsduringthe2011(Bromusspp.)meetthecriteriaofcoveringamajority(atleast50percent)ofto2015timeperiod,withover70percentofrangelandsthesoilsurfacefrom2011to2015.affectedintheStatesofCalifornia,Washington,andOregonthatcomprisethePacificCoastRegion(figure8-4,tableSource:USDANRCS2018.8-4).Cheatgrassisthemostprevalentinvasiveannualbromespecies,andhasthepotentialtodramaticallyaltertheecosystemsitinvadesbycompletelyreplacingnativevegetationandincreasingfire-returnintervals(Brooksetal.2004,Bushetal.2004,Chambersetal.2007,DiTomaso2000,Pykeetal.2016;seetheDisturbanceChapter).Cheatgrasswaspresenton18.6(±1.0)percentofnon-Federalrangelandfrom2011to2015,with50percentormoreoccupationofnon-FederalrangelandsinOregon,Washington,Idaho,Nevada,SouthDakota,andUtah(table8-4).Inadditiontoannualbromegrasses,the2018NRIRangelandResourceAssessmentindicatesthatotherannualssuchasmedusahead(Taeniatherumcaput-medusae)andventenata(Ventenatadubia)haveasignificantpresence,especiallyinthePacificCoastRegion.Likeinvasiveannualgrasses,somenonnativeperennialgrassessuchasKentuckybluegrass(Poapratensis),Canadabluegrass(P.compressa),andsmoothbromearealsonegativelyimpactingU.S.rangelandsinsomeregions.KentuckyandCanadabluegrassareperennialsod-formingTable8-4.ProportionofStateareawhereselectinvasivespeciesoccur,providedonlyforStateswhereNRIrangelandsamplesarecollected.Thevaluesinparenthesesrepresentmarginsoferrorasthe95thpercentconfidenceintervals.Estimateswithadoubleasteriskdenotethatthespecieswasnotdetectedonnon-FederalrangelandswithintheState.Someestimateswithalargemarginoferrorinrelationtotheestimatearebasedonveryfewobservations.Thelowerboundoftheconfidenceintervalmayalsobeinappropriatelynegative.StateRPAAnnualBromusPoapratensisorCentaureaandEuphorbiaJuniperusspp.ProsopisregionBromusspp.tectorumP.compressaAcropitolonspp.esulaspp.FloridaSouthLouisianaSouthOklahomaSouth20.9(5.8)6.9(3.4)TexasSouth37.3(5.4)24.2(5.9)0.5(1.1)14.5(3.8)54(4.7)Arizona6.2(1.8)1.3(0.7)11.4(5.4)ColoradoRM3.6(3)1.5(1.9)5.3(3.0)18.4(5.5)IdahoRM19.4(5.7)14.5(4.3)7.1(2.3)0.3(0.6)0.2(0.2)2.3(2.2)KansasRM72(6.1)58.1(8.6)18.1(7.2)1.8(2.2)3.9(1.4)RM57.7(5.1)32.2(4.8)39.8(5.8)8.4(4.0)MontanaRM48.9(7.1)22.2(4.3)32.1(5.6)1.4(1.1)2.3(1.6)6.3(4.0)NevadaRM52.4(12.3)52.4(12.3)1.9(3.5)2.1(3.2)5.4(2.3)37.8(4.8)0.7(0.8)14.8(3.9)NebraskaRM41(5.8)27.7(5.1)0.2(0.4)4.5(1.7)15.7(3.8)2.1(1.2)NewMexicoRM1.5(0.9)1.5(0.9)86(3.7)9.8(4.0)14.2(4.9)62.9(3.4)0.4(0.5)NorthDakotaRM9.1(3.4)0.7(0.9)9.6(5.1)0.6(1.1)1(0.7)12.2(4.1)0.2(0.5)2.6(2.2)SouthDakotaRM54(5)45.4(4.9)16.6(6.2)0.3(0.5)15.7(7.6)2.1(2.4)UtahRM53.1(7.1)51(7.4)6.9(4.5)4.1(3.4)15.8(1.3)5.6(3.8)1.1(0.4)9.4(1.2)WyomingRM47.2(6.3)31.8(5.6)14.5(0.8)0.6(0.2)CaliforniaPC73.2(8.4)9.3(4.2)OregonPC83.7(6.7)78.5(6.7)WashingtonPC87.1(5.1)82.6(6.7)National30(1.4)18.6(1.0)NRI=NationalResourcesInventory;PC=PacificCoast;RM=RockyMountain.Source:USDANRCS2018.8-6FutureofAmerica’sForestsandRangelandsspeciescommonlyplantedonpasturelands(Hall1996)butIntermsofinvasivespeciesthreatstorangelands,annualarelistedasinvasiveintheGreatPlains(Bush2002,Toledograsses,especiallycheatgrass,areoftenpositedastheetal.2014,Wennerberg2004).WhileprovidingreasonablelargestthreattoU.S.rangelands.Theyarethemostsourcesofforage,bothbluegrassspeciescandisplacenativecommonlyoccurringgroupofinvasivespeciesinnon-vegetationifnotproperlymanaged(St.Johnetal.2012,Federalrangelands(table8-4),andtheirabilitytoalterfuelToledoetal.2014).KentuckyandCanadabluegrasswerecompositionsfacilitatesfirespreadandreducesfire-returnpresenton14.5(±0.8)percentofallnon-Federalrangelandintervals(Balchetal.2013,Pilliodetal.2017),leadingtofrom2011to2015,withthelargestpresenceintheeasternlargerandmorefrequentwildfires(Chambersetal.2014).partoftheRockyMountainRegion(table8-4).TheseOtherspeciessuchasKentuckybluegrassnegativelyimpactspeciesoccupy86(±3.7)percentofnon-Federalrangelandsrangelandhealththroughreductionofbioticintegrity,eveninNorthDakotaalone.thoughtheyalsoprovidebeneficialserviceslikeofferinggoodforagefornativeanddomesticungulates.The2018NRIRangelandResourceAssessmentalsoprovidesinformationoninvasiveforbs;hereweevaluatedFederalLandsleafyspurge(Euphorbiaesula),knapweeds(Acroptionspp.),andstarthistles(Centaureaspp.).LeafyspurgeisadifficultU.S.BureauofLandManagementtoeradicate,deep-rootedinvasiveplantthatformsnearlyTheBLMmanagesapproximately98.7millionhaofFederalmonoculturalstands.ItisgenerallyconsideredpoisonoustolandsintheconterminousUnitedStatesandAlaskaforthecattleandhorsesbecauseitcontainsthealkaloideuphorbon,U.S.DepartmentoftheInterior,ofwhich78.5millionhaaknownco-carcinogenalsotoxictohumans(Washingtonarerangelands(BLM2013).TheBLMmanagesrangelandsStateNoxiousWeedControlBoard2021).However,sheeptoensuretheirhealthandproductivityfortheuseandandgoatsappearrelativelyunaffectedbytheplant.Leafyenjoymentofcurrentandfuturegenerations(PublicLawspurgewasfoundon0.6(±0.2)percentofnon-Federal95–514;PRIA1978).AlthoughtheNRIRangelandResourcerangelandsfrom2011to2015butisrelativelycommonAssessmentreportedresultsatthescaleofMajorLandinnon-FederalrangelandsinNorthDakota(table8-4).ResourceAreas,BLMrangelandsarecharacterizedhereLeafyspurgeoccursinthesamehabitatsasknapweedsandusingnineLevelIIEcoregionstomaintainconsistencywithstarthistlesinsomeareas,whichwerepresenton1.1(±0.4)otherBLMreportingefforts(Omernik1987;figure8-5).percentofnon-Federalrangelands.InCalifornia,however,BecausealmosthalfofBLM-administeredlandsfallwithinthesespeciesarefoundon16.6(±6.2)percentofnon-FederaltheColdDesertsLevelIIEcoregion,thisecoregionwasrangelands(table8-4).KnapweedsandstarthistlesinhibitfurtherdividedintoLevelIIIEcoregions:NorthernColdotherplantsthroughproductionofchemicalsubstancesDeserts,EasternColdDeserts,andCentralBasinandRangereducinggerminationorgrowth(Alfordetal.2009).Asa(Karletal.2016;figure8-5).result,knapweedsandstarthistlescanrapidlyreplacenativeInthissectionwedescribethestatusandtrendsofBLMspecies,especiallyperennialgraminoids,makinglandslessrangelandsnationallyandwithinecoregionsfrom2010resilienttodroughtandotherdisturbances.Figure8-5.LevelIIandIIIOmernikecoregionsusedfortheBLMrangelandSomenativewoodyplantspeciessuchasjunipers(Juniperushealthassessment.spp.)andmesquite(Prosopisspp.)canalsoreplacenativegrassesandforbs.Encroachmentbyshrubs,especiallyBLM=U.S.BureauofLandManagement.Juniperusspp.,hasrapidlyescalatedsincepre-Euro-Source:Omernik1987.Americansettlement(Coatesetal.2017).Theseinvasionshavesignificantlychangedfireeffectsandbehaviorwheretheyhaveoccurred,anddecreasedresiliencytodrought.Juniperspecieswerepresenton9.4(±1.2)percentofnon-Federalrangelands,withthelargestpresenceinOklahoma,followedbyOregon,NewMexico,Texas,Utah,Arizona,andMontana(table8-4).Likejunipers,mesquitespeciestypicallyhaveadeeprootsystemthatenablesthemtowithstanddroughtsandoutcompetegrasses.Honeymesquite(P.glandulosa)andvelvetmesquite(P.velutina)arethetwomostcommonspeciesfoundintheSouthwesternUnitedStates(Ansleyetal.1997).Mesquitespecieswerepresenton15.8(±1.3)percentofnon-Federalrangelands,observedmostcommonlyinTexas,Arizona,NewMexico,andOklahoma(table8-4).2020ResourcesPlanningActAssessment8-7to2020usingdatafromtheBLMLandscapeMonitoringForexample,whentheBLMreportsthat79percentofallFramework(LMF),partoftheAIMproject.TheLMFrangelandsinitsjurisdictionexhibitnone-to-moderatelevelsannualsurveyofapproximately2,000randomlocationsofdeparture,thismeansthatapproximately21percentofacrossBLMlands(Yuetal.2020)gathersinformationonBLMlandsexhibitmoderateorgreaterdeparture.Thisattributesofrangelandhealthusingthesameprocessasthecanbedirectlycomparedtotheresultsinfigure8-2(left),NRI(Pellantetal.2005),inadditiontogatheringinformationwhichshowthatnon-Federalrangelandsexhibitmoderate-onBLMterrestrialcoremetrics(Herricketal.2017)forto-extremedepartureon25.8(±1.4)percentofthelandbasereportingnational-levelstatusandtrends.Wealsoseparately(andconverselythat74percentofnon-FederalrangelandsprovidedataonthetrendofbaregroundonBLMlandsandexhibitnone-to-moderatedeparture).BytakingtheinversethepresenceofnonnativeinvasivespeciestoallowsubsequentofeithertheBLMorNRIresultswecanmakedirecthealthcomparisonwithconsistentnational-leveltrendsderivedfromcomparisonsbetweenBLMandnon-Federalrangelands.remotesensinginthesectionAllLandsTrends.Percentcoverofbaregroundwasdeterminedusingtheline-pointinterceptRangelandHealthmethod(Herricketal.2017)whilepresenceofnonnativeinvasivespeciesisderivedfromthespeciesinventorymethodTheLMFrangelandhealthassessmentsshowthatthemajority(Herricketal.2017).ofBLMrangelandsarerelativelyhealthy,withonlynone-to-slightorslight-to-moderatedeparturefromreferenceResultsoftheBLMrangelandhealthassessmentareprovidedconditionsintermsofanyoneattribute(figures8-6,8-7,aseithertheproportionoftheareawithinaconditionclass8-8).Between79and86percentofBLMrangelandsfromorasanaveragestatusacrossthearea,andareweighted2011to2018exhibitedless-than-moderatedeparturefrombasedontheBLMlandareasampled.Eachindicatorreferenceconditionsforthethreerangelandhealthattributesestimateispresentedusingfourcategoriesofdeparturefrom(figures8-6,8-7,8-8).Conversely,14to21percentofBLMreferenceconditions(similartotheNRIRangelandResourcerangelandsexhibitedmoderate-to-extremedepartureinAssessment):(1)none-to-slightorslight-tomoderateoneofthethreerangelandhealthcategories.Ofthethreedeparturefromreferenceforbioticintegrity,(2)none-to-slightrangelandhealthattributes,bioticintegrityexhibitedtheorslight-tomoderatedeparturefromreferenceforhydrologichighestvalues(i.e.,hadthegreatestamountofdeparture),function,(3)none-to-slightorslight-to-moderatedepartureconsistentwithnon-Federallands.fromreferenceforsoilandsitestability,and(4)none-to-slightorslight-to-moderatedeparturefromreferenceforComparedtonationalconditions,theWesternCordilleraandbioticintegrity,hydrologicfunction,andsoilandsitestability.theWest-CentralSemiaridPrairieshavealargerpercentageAlthoughthesamerangelandhealthevaluationprocessisofBLMrangelandinbettercondition(moreareawithnone-usedbyboththeBLMandNRI,thesetwoprogramsreportto-slightorslight-to-moderatedeparturefromreferencefortheirofficialresultsslightlydifferently.TheBLMfocusesatleastoneattributeofrangelandhealth),whiletheWarmonproportionofhealthyrangelands,framingandreportingDesertshavealargerpercentageofrangelandinworserangelandhealthintermsofnone-to-slightorslight-to-condition(lessareawithnone-to-slightorslight-to-moderatemoderatedeparturefromreferenceconditions.Incontrast,departurefromreference).Rangelandhealthattributesthe2018NRIRangelandResourceAssessmentresultsspanappeartobestableorimprovinginallecoregions.Thesethescoringspectrum,althoughmostofthefiguresfocusonBLMrangelandhealthresultssupporttheresultsfoundunhealthyrangelandsbyshowingonlymoderate-to-extremeonnon-Federalrangelands,howeverthewideconfidencedepartures.Eventhoughthesesimilardataareportrayedintervals(figures8-6,8-7,8-8)suggestthatsometrendsmayanddescribedfromoppositeendsoftherangelandhealthnotbesignificantandmoreresearchisneededtoestablishscoringperspective,theycanbeinterpretedthesameway.thelevelofsignificance.8-8FutureofAmerica’sForestsandRangelandsFigure8-6.PercentofBLMrangelandswherebioticintegrityexhibitsnone-to-slightorslight-to-moderatedeparturefromreferenceconditions(80percentconfidenceinterval).Theremainingrangelandareacorrespondstorelativelyhigherdeparture.AllBLMRangeArizona/NewMexicoMountainsCentralBasinandRangeEasternColdDesertsPercentofrangelandacresonBLM-administeredlandsMadreanArchipelagoMediterraneanCaliforniaNorthernColdDesertsSouth-CentralSemaridPrairiesWarmDesertsWest-CentralSemiaridPrairiesWarmDesertsBLM=U.S.BureauofLandManagement.X=Estimatesunavailableduetosmallsamplesize(fewerthan10samples)Source:Yuetal.2020.YearFigure8-7.PercentofBLMrangelandswheresoilandsitestabilityexhibitsnone-to-slightorslight-to-moderatedeparturefromreferenceconditions(80percentconfidenceinterval).Theremainingrangelandareacorrespondstorelativelyhigherdeparture.AllBLMRangeArizona/NewMexicoMountainsCentralBasinandRangeEasternColdDesertsPercentofrangelandacresonBLM-administeredlandsMadreanArchipelagoMediterraneanCaliforniaNorthernColdDesertsSouth-CentralSemiaridPrairiesWarmDesertsWest-CentralSemiaridPrairiesWarmDesertsYearBLM=U.S.BureauofLandManagement.X=Estimatesunavailableduetosmallsamplesize(fewerthan10samples)Source:Yuetal.2020.2020ResourcesPlanningActAssessment8-9Figure8-8.PercentofBLMrangelandswherehydrologicfunctionexhibitsnone-to-slightorslight-to-moderatedeparturefromreferenceconditions(80percentconfidenceinterval).Theremainingrangelandareacorrespondstorelativelyhigherdeparture.AllBLMRangeArizona/NewMexicoMountainsCentralBasinandRangeEasternColdDesertsPercentofrangelandacresonBLM-administeredlandsMadreanArchipelagoMediterraneanCaliforniaNorthernColdDesertsSouth-CentralSemiaridPrairiesWarmDesertsWest-CentralSemiaridPrairiesWarmDesertsBLM=U.S.BureauofLandManagement.X=Estimatesunavailableduetosmallsamplesize(fewerthan10samples)Source:Yuetal.2020.Year8-10FutureofAmerica’sForestsandRangelandsInvasiveSpecies2015)aremostaffectedbynonnativeinvasivespecies,whichareincreasinginpresenceacrosstheseecoregions(figure8-9).NonnativeinvasivespeciesoccurredonBLMrangelandsinallIntheMediterraneanCaliforniaecoregion,althoughthesampleecoregions,presentonabouthalfandabundant(≥25percentsizehasbeentoosmallforinclusioninfigure8-9inmostyears,absolutefoliarcover)on15.8millionhaofBLMrangelandsnonnativeinvasivespeciespresencewas100percentin2015.in2018(table8-5).NonnativeinvasivespeciesappeartobeIncreasesinnonnativeinvasivespeciesalsooccurredintheconstantorincreasingfornearlyallecoregionsexceptSouth-WarmDesertandWest-CentralSemiaridPrairieecoregionsCentralSemiaridPrairies.TheNorthernColdDeserts,Central(figure8-9),whiletheamountofbaregroundintheseareashasBasinandRange,andMediterraneanCalifornia(atleastforgenerallydecreased(figure8-10).Table8-5.EstimatedBLMrangelandareawherenonnativeinvasivespecieswerepresentandabundant(absolutefoliarcover≥25percent)in2018.The-indicatesinsufficientdatatomaketheestimate.EcoregionNonnativeinvasivespeciespresentAbsolutefoliarcovercomposedof≥25%nonnativeinvasivespeciesArizona/NewMexicoMountainsCentralBasinandRangeamillionhastandarderrormillionhastandarderrorEasternColdDeserts--MadreanArchipelagoa--MediterraneanCaliforniaa13.80.69NorthernColdDesertsa7.430.486.030.9South-CentralSemiaridPrairiesWarmDeserts--2.320.55West-CentralSemiaridPrairies0.380.38WesternCordillera8.890.3--AllBLMLands0.110.123.120.480.380.38aLevelIIIecoregion.2.460.26BLM=U.S.BureauofLandManagement;ha=hectares.1.670.55.020.44Source:Yuetal.2020.37.861.33--0.820.260.710.210.580.3415.871.27Figure8-9.PercentofBLMrangelandswithpresenceofnonnativeinvasiveplantspecies(80percentconfidenceinterval).SeeKarletal.(2016)foralistofplantspeciesconsiderednonnativeinvasivespecies.AllBLMRangeArizona/NewMexicoMountainsCentralBasinandRangeEasternColdDesertsPercentofrangelandacresonBLM-administeredlandsMadreanArchipelagoMediterraneanCaliforniaNorthernColdDesertsSouth-CentralSemiaridPrairiesWarmDesertsWest-CentralSemiaridPrairiesWarmDesertsYearBLM=U.S.BureauofLandManagement.X=Estimatesunavailableduetosmallsamplesize(fewerthan10samples)Source:Yuetal.2020.2020ResourcesPlanningActAssessment8-11Figure8-10.AveragebaregroundcoveronBLMrangelands(80percentconfidenceinterval).AllBLMRangeArizona/NewMexicoMountainsCentralBasinandRangeEasternColdDesertsPercentcoverofbaregroundonBLMrangeMadreanArchipelagoMediterraneanCaliforniaNorthernColdDesertsSouth-CentralSemiaridPrairies➤WarmDesertsWest-CentralSemiaridPrairiesWarmDesertsBLM=U.S.BureauofLandManagement.X=Estimatesunavailableduetosmallsamplesize(fewerthan10samples)Source:Yuetal.2020.YearUSDAForestServiceFigure8-11.SpatialdistributionofAllConditionsInventory(ACI)plots,administeredbytheUSDAForestServiceForestInventoryandAnalysisTheUSDAForestServicehasconductedtheFIAAllProgramthroughouttheWesternUnitedStates.ConditionsInventory(ACI)sporadicallyonNationalForestSystemlandsintheWesternUnitedStatessince2004.UnlikeNtheNRIandAIMprojects,theACIprotocolsdonotevaluateSource:Bush2012.rangelandhealthattributessonoformalcomparisoncanbemadewithnon-Federal(NRI)orBLM(AIM/LMF)lands.Inaddition,notallnationalforestsparticipateinthisprogram.Approximately1,400ACIplotshavebeenestablishedthroughoutUSDAForestServiceRegions1(northernIdaho,westernMontana)and4(southernIdahoandUtah)asofJuly2017(figure8-11).Ofthese,113plots(8.1percent)wereremeasuredwithin10yearsoftheirinitialinstallation(91plotsinRegion1and22plotsinRegion4;table8-6).ACIplotswerefoundinall21nationalforestsinUSDAForestServiceRegions1and4(table8-7).Onlylimitedinferencescanbemadegiventherelativelysmallsamplesizeandplotdensityandthelownumberofplotsthatwererevisitedatthetimeofthisanalysis(2017).Wecanconfirmthepresenceofkeyinvasivespeciessuchascheatgrass,knapweed,toadflax(Linariadalmatica),andleafyspurgeinplotsacrosstheseregions;allofthesespecieshavethepropensitytosignificantlychangeecologicalconditions.Forallplotswithinitialmeasurements,217plotscontainedatleastoneofthefourkeyinvasiveplants,with21plotsoccurringinRegion1and196inRegion4.Cheatgrasswasmostprevalent,occurringin215oftheseplots(table8-7).Plotswithcheatgrasshadaweightedaveragecheatgrassfoliarcoverof5.9percentacrossallACIplots.8-12FutureofAmerica’sForestsandRangelandsTable8-6.DistributionofACIplotsandassociated2005to2017(tables8-4,8-7).ThePayetteandSawtoothNationalForestsremeasurementinformation,byUSDAForestServiceregionandState.inIdahohadthehighestmeancheatgrasscover,eachwithapproximately12-percentcoverandanoccurrencerateinUSDAForestLocationACIplotsRemeasuredACIplotsof38and19percent,respectively.Incomparison,ServiceRegioncheatgrasswasfoundon58(±8.6)percentofnon-FederalrangelandsinIdaho(table8-4).WhiletheACIandNRIbothnyieldvaluableinformation,differencesinsamplesizeandsampledesignmeanthatthedataarenotdirectlycomparable1NorthernIdaho427andlimitourabilitytomakestatisticalcomparisonandinferences.Inaddition,landsmanagedbytheUSDAForest1Montana22584Servicearetypicallyhigherinelevationthanthenon-Federalcounterpartsandcheatgrasscurrentlyexhibitspreferencesfor4Nevada3720lowerelevation(warmeranddrier)landscapes.Asaresult,thefindingscouldreflectthebiophysicalpreferencesofcheatgrass4Utah21220forrelativelywarmerlowerelevationsites,moresothanlandusehistory.AlthoughthisintroductiontotheACIprogram4SouthernIdaho4122doesnotquantifyrangelandhealthonUSDAForestServicelands,itraisesawarenessofdatathathavepreviouslybeen4Wyoming1370underutilizedforrangelandassessments.Total1,400113ACI=AllConditionsInventory.Source:Bush2012.Thesefindingsshowcheatgrassoccurringon15percentofthesampledareawithinUSDAForestServicerangelands,lessthanthe18-percentoccurrenceonnon-FederalrangelandsTable8-7.TotalnumberanddensityofAllConditionsInventory(ACI)plotsinUSDAForestServiceRegions1and4.NumberofplotsandmeanfoliarcoverofcheatgrassoccurringoninitialmeasurementACIplotsarealsoprovided.Plotswithnocheatgrassareindicatedby“-”.Plotdatacurrentasof2017.USDAForestForestnameACIplotsPlots/PlotswithFoliarcoverofServiceRegionmillionacrescheatgrasscheatgrass(%)Bitterroot111IdahoPanhandle76.6110.81NezPerce-Clearwater302.4--1Boise447.478.84Caribou-Targhee11217.4225.64Payette2636.473.94Salmon-Challis13310.8104Sawtooth10830.32511.84Beaverhead-Deerlodge8549.3216.41Custer-Gallatin8923.5-12.21Flathead1126.17-1Helena-LewisandClark224.2-3.71Kootenai56.93-1Lolo71.9-3.51Humboldt-Toiyabe3722.71-4Ashley4655.5821.34Dixie3632.873.74Fishlake4521764Manti-LaSal3125.285.84Uinta-Wasatch-Cache5521.9-8.84Bridger-Teton11518.94-4RMRSDesertExperimentalRange1033.2-1.541,400179.63Total(average)(23)215(5.9)ACI=AllConditionsInventory;RMRS=RockyMountainResearchStation.Source:Bush(2012).2020ResourcesPlanningActAssessment8-13AllLandsTrendsFigure8-12.Correlationof(a)perennialforbandgrasscover,(b)annualforbandgrasscover,and(c)baregroundwithrespecttotimeonrangelands,Whilenational-levelsamplingprogramsoffervaluablederivedusingPearson’srfrom1984to2020forecologicalsubsectionsinformationaboutthestatusofU.S.rangelands,theydo(BaileyandHogg1986).NegativePearson’srvaluescorrespondtodecliningnotprovidethespatialortemporalresolutionneededtotrends.RangelandAnalysisPlatformdataarenotavailablefortheEasternevaluaterangelandtrendsconsistentlyforallownerships.UnitedStates.ThewidespreadavailabilityofremotelysenseddataandthedramaticincreaseincomputationalpoweroverthelastaTrendinperennialgrassandforbcover(1984to2020)fewdecadeshasimprovedthecapabilityforrangelandtrendanalysis.InthissectionwehighlightthesenewbTrendinannualgrassandforbcover(1984to2020)capabilitiesbydescribingtrendsofannualforbandgrasscover(AFGC),perennialforbandgrasscover(PFGC),bareground(BG),netprimaryproductivity(NPP),andinterannualvariabilityofNPP.EvaluationofAFGC,PFGC,andBGcomefromtheRangelandAnalysisPlatform(RAP)(Jonesetal.2018)duetoavailabilityontheGoogleEarthEngineplatform,althoughtheU.S.GeologicalSurveyBackinTimedata(Homeretal.2020,Riggeetal.2021)couldalsohavebeenused.TheNPPdatacomefromtheRangelandProductivityMonitoringService(RPMS)(Reevesetal.2020).RangelandCovercTrendinbareground(1984to2020)EvaluatingtrendsinAFGC,PFGC,andBGcanindicateSource:RangelandAnalysisPlatform(Jonesetal.2018).(20May2021).emergingproblems,suchasreducedrangelandhealthorreducedresiliencytodroughtorclimatechange.Byexaminingchangesinthefoliarcoverofdifferentlifeformsandcoverofbareground,wecanmakegeneralstatementsabouttheconditionofthelandscape.Forexample,decreasesincoverofperennialspeciessuggestsreducedrangelandhealth,carryingcapacity,andresiliencytodrought.Toperformthisanalysis,wecalculatedthelineartrend(correlationwithrespecttotime;Pearson’sr)ofAFGC,PFGC,andBGfrom1984to2020acrossmostrangelandsoftheconterminousUnitedStates.Whiletheoriginaldatawereavailableata30-mresolution,weaggregatedtheinformationtoBailey’secoregionsattheecologicalsubsectionlevel(BaileyandHogg1986),andtoOmernikregions(table8-8)andtheMajorLandResourceAreasusedpreviouslyforcomparativepurposeswiththeAIM/NRIanalyses.Becausepreliminaryanalysissuggestedthatthepost-2000periodusheredinsignificantchangesinrangelandsoftheconterminousUnitedStates,wedividedthetimeseriesintotwoperiods(1984to1999and2000to2020)toconfirmwhenmostofthechangesinrangelandattributestookplace.Attheecologicalsubsectionsspatialscale(BaileyandHogg1986),PFGCisstronglyincreasingonthenorthernGreatPlains,principallyeasternMontana,mostofNorthDakota,andnorthernSouthDakota(figure8-12),dueinparttosignificantincreasesingrowingseasonprecipitation(Reevesetal.2020).ThemostwidespreaddeclinesinPFGCoccurinCalifornia,mostofUtah,western8-14FutureofAmerica’sForestsandRangelandsColorado,andwesternMontana.IncontrasttodeclinesTable8-8.Correlationofperennialforbandgrasscover(PFGC),annualinPFGC,AFGChasincreasedinmagnitudeandextentforbandgrasscover(AFGC),andbareground(BG)withrespecttotimethroughoutmuchoftheWest.Thesignificantincreasesonrangelands,derivedusingPearson’srfrom1984to2020forOmernik’sinAFGCarelikelyduetoinvasiveannualgrassessuchecoregions.NegativePearson’srvaluescorrespondtodecliningtrends,ascheatgrass,redbrome(Bromusrubens),andventenatawhilepositivenumbersindicateanincreasingtrend.Largernumbersnotedthroughoutthisassessment.EasternWashingtonindicateahigherpositivecorrelationofcoverovertime(coverisgoingupandOregon,aswellassouthernIdaho,centralUtah,andovertime).northernNevadahaveexperiencedthegreatestincreasesinAFGC,withadditionalincreasesfoundineasternMontanaOmernikLevelIIRangelandPFGCAFGCBGandWyoming(figure8-12).ThesefindingsareconsistentEcoregionsampledwithrecentevidencesuggestingthatannualgrassesaremillionhacorrelation(r)expandingacrosstheWest,includingathigherelevationsAllRangelands124.9thanpreviouslyexpected(Nicollietal.2020,PawlakArizona/NewMexico-0.30.3-0.3etal.2014).Mountains2CentralBasinandRange-0.10.10Evaluationofthetwoseparatetimeperiods(1984toEasternColdDeserts11.81999and2000to2020)revealsthatmostchangesintheMadreanArchipelago15.7-0.40.4-0.4remotelysensedrangelandindicatorshavetakenplaceMediterraneanCalifornia1.7since2000.ThenationalaverageforbothPFGCandBGNorthernColdDeserts3.5-0.30.2-0.2werereducedbyapproximately8percentwhencomparingSouth-CentralSemiarid10.81984to1999with2000to2020.Seventy-threepercentofPrairies-0.20.3-0.1rangelandsexperiencedlossesofPFGCfrom2000to2020,WarmDeserts28.5while72percentofrangelandsexperienceddecreasesofWest-CentralSemiarid-0.50.5-0.2BG.Incontrast,thenationalaverageforAFGCincreasedPrairies17.9by15percentwhencomparingtheperiod1984to1999WesternCordillera-0.20.6-0.4versus2000to2020.Eighty-fivepercentofrangelands23.9experiencedincreasesofAFGCfrom2000to2020relative00.1-0.2to1984to1999.Thesedatacoincidewiththedistribution9.1ofinvasiveannualbromesfoundonnon-Federallandinthe-0.50.2-0.3NRIRangelandResourceAssessment(figure8-4).0.10.3-0.5Thewidespreadincreasesinannualforbsandgrassesaredirectlyresponsiblefortheaccompanyingdecreasesinbare-0.30.3-0.3groundovermuchoftheWesternU.S.rangelands(figure8-12).DecreasesinbaregroundareoftenconsideredSource:RangelandAnalysisPlatform(Jonesetal.2018).(20May2021).positive,indicatingthatannualNPPislikelyincreasingoratleastmaintainingyields.Manyofthesedecreasesinbarewithconcomitantdecreasesinbaregroundasaresult(tableground,however,arerelatedtoincreasesininvasiveannual8-8).Notabledifferencesbetweentheremotelysenseddataforbsandgrasses,whicharecausingsignificantecologicalandthosefromAIMincludethefactthatremotelysensedchangesmanifestedthroughincreasedfirefrequenciesdatacoverallrangelandownershipswhileAIMcoversonlyandbehavior(Pilliodetal.2017),andchangesinforageBLMlandsandthatBGistheonlyattributeapproachedquantity,quality,andphenology.ThemajorityofU.S.consistentlybybothefforts.rangelandshavebeenexhibitingdecreasingbaregroundtrendssince1984.WhilemostrangelandshaveexhibitedRangelandAnnualProductionsomedecreaseinbareground,therearesomenotableexceptions,includingtheareasofwestTexasandmostofNetprimaryproductivityisacriticalindicatorofrangelandNewMexico(figure8-12).health,anditservesasforagefornativeanddomesticungulates,smallmammals,andinsects.TheRPMSThisremotelysensedevaluationofrangelandcomponentsprovidesspatiallyexplicitestimatesofrangelandNPPhasalsobeensummarizedacrosstheOmernikecoregions,toacrosstheconterminousUnitedStatesfrom1984to2021allowcomparisonwiththeAIMrangelandhealthevaluationandbeyond,ata30-mspatialresolution,but2020isthe(table8-8).Forexample,theincreaseininvasivespeciesmostrecentdataincludedinthisreportbecauseoftheRPAintheCentralBasinandRangeonBLMlands(figure8-9)productionschedule.Usingthesedata,wequantifiedthecorrespondswiththefindingthatAFGCisincreasingonaverageNPPvalues,trendinNPPvalues,andinterannualallrangelandsintheCentralBasinandRange(r=0.44),variability(standarddeviationofthetimeseriescomparedtothemean).Becausetrendsandvariabilityfrom1984to1999differfromresultsforthe2000to2020timeperiod(Reevesetal.2020),weanalyzedrangelandNPPtrendsandvariabilityforthreetimeframes:1984to2020,1984to1999,and2000to2020.Aswiththeanalysisofthetrendsincoverdata,wecalculatedthelineartrendofNPP(correlationwithrespecttotime;Pearson’sr).2020ResourcesPlanningActAssessment8-15IncreasesinannualNPPhaveoccurredinallRPAregionsFigure8-13.Correlationofannualnetprimaryproductivitywithrespecttotimesince1984(table8-9).ThehighestNPPvalues(>4,400onrangelandsderivedusingPearson’srfrom(a)1984to2020,(b)1984to1999,kgha-1)wereobservedintheNorthRegion.Conversely,and(c)2000to2020.NegativePearson’srvaluescorrespondtodecliningtrends.theRockyMountainRegionexhibitedthelowestNPPvalues(1,140kgha-1).Interannualvariabilitywashighesta(1984to2020)intheSouthandPacificCoastRegions,withcoefficientsofvariability(CV)of0.17and0.16,respectively,meaningb(1984to1999)thatNPP(andforage)variedabout17percentannuallyonaveragefrom1984to2020.VariabilityinNPPwashigherc(2000to2020)from2000to2020comparedto1984to1999—withbothhigherhighsandlowerlowsinNPP—whileNPPtrends,Source:RangelandProductionMonitoringService(Reevesetal.2020).(20May2021).whichwerepositivefrom1984to1999,stagnatedordeclinedfrom2000to2020.Thesebroadnationalandregionalaverages,however,masktrendstakingplaceonrangelandsatthesubregionallevel(figure8-13).Inalltimeperiods(1984to2020,1984to1999,and2000to2020)thedesertSouthwestexhibiteddecliningtrendsinNPP.Incontrast,increasesinNPPoccurredeastoftheCascadeMountainsinthePacificNorthwestandthenorthernGreatPlainsofNorthDakota,SouthDakota,andMontana(Reevesetal.2020,figure8-13).InadditiontotheseasymmetrictrendsinannualNPP,interannualvariabilityafter2000wasgreaterthanfrom1984to1999forallregions(table8-9).Thecauseofincreasedvariabilityisnotknownbutcouldbelinkedtomoreintenserainfalleventsandgreateroccurrencesofextremetemperatures(Frameetal.2020).TheincreasedvariabilityinannualNPPhassignificantimplicationsforrangelandforagesupplies.Weestimatedforagequantity,therelativeproportionofherbcovertototalvegetationcover,andauniversalestimateofforagebeneathforestcanopiesusingRPMSdata.Foragequantitiesonrangelandswereestimatedforaverage,above-average,andbelow-averageforageconditions,calculatedastheaverageplusorminusonestandarddeviationfromthemeanfrom1984to2020.Keyassumptionsmadeintheanalysisareoutlinedintable8-10.Privatelandsarethelargestcontributortorangelandforagepools(table8-10),duetoboththelargeextentofprivaterangelands(55percent)relativetopublicrangelands(table8-2)andthehigherNPPratesrelativetootherjurisdictions.Table8-9.RangelandNPPcharacteristicsincludingmean,coefficientofvariability(ameasureofinterannualvariability),andcorrelation(r)withrespecttotimeforthreeperiods:1984to2020,1984to1999,and2000to2020.1984to20201984to19992000to20201984to20201984to19992000to20201984to20201984to19992000to2020Meankgha-1Correlation(Pearson’sr)RPAregion4,4024,620Coefficientofvariability1,5904,1251,720North1,1401,4101,207percentSouth1,3001,0431,399RockyMountain1,1680.080.050.070.750.580.07PacificCoast0.170.130.150.560.330.070.140.130.130.600.420.270.160.140.150.530.37-0.05ha=hectares;kg=kilograms;NPP=netprimaryproductivity.Source:RangelandProductionMonitoringService(Reevesetal.2020).(20May2021).8-16FutureofAmerica’sForestsandRangelandsTable8-10.TotalforagebyownershipandlandcoverclassandtheassociatednumberofanimalunitstheselandscansupportonanannualbasisunderdifferentconditionsintheconterminousUnitedStatesfrom1984to2020.AveragetotalAverageAveragetotalNPPAverageAverageAverageNPP(favorabletotalNPPherbaceousherbaceousNPPOwnershiporManagement(unfavorableherbaceousNPPconditions)32.9NPP(unfavorableconditions)(favorableconditions)conditions)214.2teragrams14.6182U.S.BureauofLand42.22.623.626.120.40.7Management2.27.7U.S.NationalParkService2.614.41.41.3198.6Tribal18.5919.914.811.21Privateland236.7341.3127.2184.5141.60.9U.S.Army3.5151.31.72.11.65.8U.S.FishandWildlifeService2.91.61.71.347USDAForestService18.164.310.7107.9176.3Other1186487.567.2151.3Rangelandtotal442.5240328.1252.2Pasturesa151.3151.3151.3151.364.3Foragebeneathforestedcanopiesb64.364.364.364.3329Totalforage(rangeland,pasture,forests)721556391606467225,342,46738,082,19231,986,301AUYfromallforagepoolsd49,383,562estimatedanimalunitsperyearc26,780,82241,506,849Assumptions:aThenationalannualaverageyieldfrompasturesof3,235kgha-1(2,886poundsperacre)wasderivedfromRPMS(Reevesetal.2020).Irrigatedpasturesarenotincludedonthisassessment.bInareasnotconsideredrangelandandwheretreecanopycoverexceeded1percentweassumedaconservativeforageestimateof241kgha-1(215poundsperacre)(Gainesetal.1954,ReevesandMitchell2012).cAnanimalunitisdefinedasonematurecowofabout450kg,eitherdryorwithcalfupto6monthsofage,andhasageneralnutritionalrequirementofabout12kgofdrymatterperday(Smithetal.2017).Weassumedthat30percentoftheforageinagivenyearcouldbesustainablyharvestedtosupportanimals.dExcludingagronomicallyderivedfeedstuffssuchascornorsoymeal.AUY=animalunitsperyear;kg=kilogram;NPP=netprimaryproductivity;RPMS=RangelandProductivityMonitoringService.Source:RangelandAnalysisPlatform(Jonesetal.2018)(20May2021)andRangelandProductionMonitoringService(Reevesetal.2020).(20May2021).ThehigherNPPratesonprivatelandsreflectthespatiallyidentifiedinReevesandMitchell(2011).TransitionalexplicitsettlementpatternsoftheWesternUnitedStates;rangelandsarelandswherethedominantvegetationisshrubsthemostproductivelandswereusuallyprivatizedduringandgrasses,butbecausethesitewilltransitiontoforestitdoessettlementwhilelessproductiveareas—areaspredisposedtonotmeetthecriteriaforbeingclassifiedasrangeland.InsomereducedNPPduetoabioticfactorssuchasdrierclimatology,regions,transitionalrangelandsrepresentlargepoolsofforagethinsoils,andjuxtapositiononthelandscape(e.g.,rainsuitableforherbivory,buttheircontributiontotheforagebaseshadow)—wereleftinthepublicdomain.ProductionisrelativelysmallerandephemeralfromanationalperspectiveonUSDAForestServicelandaverages1,544kgha-1,(Allen1988).approachingthelevelofnon-Federallands(1,614kgha-1)andmorethantwicethelevelofBLMproductivity(622kgTheanimalunitsthatcanbesupportedannually(animalha-1).RangelandsmanagedbytheUSDAForestServicetendunityear)bythistotalforagepoolrangesfrom45to84tooccuronhigherelevations,whichtypicallyreceivegreatermilliondependingonthegrowthconditions(below-average,precipitationthanlowerelevationlandscapes.Despiteloweraverage,orabove-averageproductionyear).NotalllivestockNPP,theBLMisthesecondlargestproducerofforageinreceivesustenancesolelyonrangelands,however;manyconterminousUnitedStatesrangelandsduetothelargelivestockalsoconsumehayorotheragronomicallyderivedextentoflandsunderitsjurisdiction(table8-10).feedstuffssuchascorn,oats,andbarley.ThisisespeciallytrueforpubliclandpermitteeswhooftenhaveonlyTheaverageannualrangelandforagepoolacrossalltemporaryaccesstopubliclandforageandareeventuallyrangelandsintheconterminousUnitedStatesisroughly341.3requiredtomovelivestockinaccordancewiththetermsTg,including252.2Tgofherbaceousforage(table8-10;oftheirpermits,orinareaswheresnowfalllimitsaccessReevesetal.2020).Theaverageannualpastureforagepooltoforage.Thisanalysisalsodoesnotaccountforforageis151.3Tg(table8-10)andtheforagepoolbeneathforestedthatmaybeunavailableduetoterrainordistancefromcanopiesisapproximatedat64.3Tg.Theseforagecalculationswaterwhichmayprohibitsomeclassesofungulatesfromdonotincludeareasdominatedbytransitionalrangelandsaccessingsomeforage.2020ResourcesPlanningActAssessment8-17LivestockTrendsFigure8-15.Numberofsheep,meatgoats,andAngoragoatsintheconterminousUnitedStates.❖TheaveragenumberofcattleintheconterminousSheepandmeatgoatnumbers(millions)Angoragoatnumbers(thousands)UnitedStatesdecreasedalmost30percentbetweenthe1975peakand2020.DespitetheseYeardeclines,thebeefyieldhasremainedrelativelysteady,attributabletolargercattle.Source:NASS2021.(20May2021).ThenumberofcattleintheUnitedStatespeakedatabout132millionin1975,followedbyacontinualdecline(figure8-14).By2020theaveragenumberofcattleintheconterminousUnitedStatesdecreasedalmost30percenttoapproximately93million.Despitethisdecline,totalbeefproductionremainedstableduetoincreasedefficienciesleadingtolargercattle,includingadvancesingrowthenhancers,feedmilling,andfeedadditives.TheaverageyearlingbodyweightofAngusbreedbullsandheifersincreasedfromtheearly1970stothemid-2000sby3.6and2.6kgperyear,respectively(OhioCountryJournal2017,NASS2021).Figure8-14.NumberofbeefcattleintheconterminousUnitedStates,nationallyandbyRPAregion.CattlenumbersforRPAregions(millions)CattlenumbersforconterminusU.S.(millions)OutlookforRangelandsYearThissectionfocusesontheimpactsofclimatechangeonrangelandphenology,NPP,andlanduse.ChangesinSource:NASS2021.(20May2021).thesevegetationmetricsandusepatternswereestimatedundertwoboundingclimatefutures:RepresentativeCattleproductioninthePacificCoastandRockyMountainConcentrationPathway(RCP)4.5,whichrepresentsaRegionsremainedrelativelysteadyoverthistimeperiod,lowerwarmingfuture,andRCP8.5,whichrepresentsawhiletheNorthRegionexperiencedthelargestdeclineshigh-warmingfuture.Wepairedthesetwoclimatefutures(figure8-14).TheSouthRegion,whichwassignificantlywithfivedifferentclimatemodelsthatcapturetherangeimpactedbydroughtsduring2011and2012,experiencedofprojectedfuturetemperatureandprecipitationacrosssomereboundsincattlenumbersfollowingthoseyears,theconterminousUnitedStatestoprovide10distinctbutnotenoughtoreverselong-termdecline.Thenumberclimateprojections(twoRCPs,fiveclimatemodels).ofsheepintheconterminousUnitedStateshasdeclinedThefiveclimatemodelsselectedbyRPArepresentleastevenmorerapidly:sheepnumbershavedecreasedabout74warm,hot,dry,wet,andmiddle-of-the-roadclimatepercentsince1970(toanaverageof5.3millionsince2015).futuresfortheconterminousUnitedStates(table8-11);Whilecommerciallyraisedgoatshavenotbeenmonitoredhowever,characteristicscanvaryatfinerspatialscales.foraslongascattleandsheep,bothmeatgoatsandAngoraTheScenariosChapterdescribeshowtheseclimatemodelsgoatshaveseendeclinesof15and37percent,respectivelywereselected;JoyceandCoulson(2020)providemoresince2008(figure8-15).extensiveinformation.Tofacilitateinterpretation,althoughwerunouranalysesusingeachRPAclimateprojection,weonlypresentminimumandmaximumresultsbelow(eachtheresultofusingadifferentclimateprojection),aswellasanensembleresultthatreducescomplexitybyprovidingtheaverageamountofchangeprojectedforvariousattributesacrossclimateprojectionsandacrossU.S.rangelands(performedforRCP4.5andRCP8.5separately).Wealsoexaminehowtointerpretprojectedchangesinclimateusingstatisticalanalogs.Thegoalofthesestatisticalanalogsistoidentifywhatcity(orlocation)todaybestrepresentstheexpectedfutureclimateofagivencityby2080.8-18FutureofAmerica’sForestsandRangelandsTable8-11.FiveclimatemodelsselectedtoreflecttherangeofU.S.climatefuturesintheyear2070.EachmodelwasrununderRCP4.5andRCP8.5,andthereforeprovidesdistinctclimateprojectionsforeachRCP.ClimatemodelLeastwarmHotDryWetMiddleInstitutionMRI-CGCM3HadGEM2-ESIPSL-CM5A-MRNorESM1-MCNRM-CM5MeteorologicalResearchMetOfficeHadleyInstitutPierreSimonNationalCentreofNorwegianClimateInstitute,JapanCentre,UnitedKingdomLaplace,FranceMeteorologicalResearch,Center,NorwayFranceRCP=RepresentativeConcentrationPathway.Source:JoyceandCoulson2020.ProjectionsofRangelandPhenologyTheimpactofclimatechangeonrangelandphenologyisrelativelyunderstudiedatthenationallevel;however,❖Growingseasonsareprojectedtobe3to4daysspatiallyexplicitmetricsofkeyphenologicalattributes,includingstartofseason(SOS),endofseason(EOS),andshorterbyearlycenturyand6to10daysshorterlengthofvegetationgrowth(referredtohereasthegrowingbymid-century,primarilyduetonutrientlimitations.season),areavailablefortheperiodbetween2000to2020LocalgrowingseasonscouldbereducedbyasfromtheU.S.GeologicalSurvey(https://www.usgs.gov/muchas20daysundertheRCP8.5ensemblecore-science-systems/eros/phenology)(Guetal.2010).scenario.Tobetterunderstandpotentialfuturechangesinrangelandphenologyweusedthesedatatomodelfuturechangesin❖EarlierprojectedshiftstothestartoftherangelandSOSandEOS(Zimmeretal.2022).ThephenologymodelsdevelopedinZimmeretal.(2022)relateaseriesofabioticgrowingseasonaremostpronouncedineasternandbioticpredictorstoSOSandEOSincludingvegetationWashingtonandOregonandthroughouttheGreattype,elevation,andbasicclimaticforcing,includingsolarBasin,relativetootherareas.radiation,maximumtemperature,vaporpressuredeficit,andaccumulatedgrowingdegreedays(Zimmeretal.❖Earlierprojectedshiftstotheendofthegrowing2022).Relativelylittlemodelingwasconductedindesertareas,particularlytheSonoranandChihuahuandeserts,seasonaremorepronouncedthanchangestobecausephenologyisnotoriouslydifficulttocharacterizethestartofthegrowingseason,especiallyontheintheseareas(Zimmeretal.2022).Inaddition,vegetationsouthernplainsofTexasandOklahomawherethephenologyintheNorthRegionwasnotmodeledduetoendoftheseasonisprojectedtooccurupto31alackofavailabledatafromGuetal.(2010).Resultsdaysearlierby2070underRCP8.5.portrayedhererepresentthechangeinJuliandayscomparedagainstthe2000to2014baselineperiod(selectedduetoPhenology—thetimingofplantlifecycleevents—influencesdataavailabilityatthetimeofanalysis).theabundanceanddistributionoforganisms,ecosystemservices,foodwebs,andglobalcyclesofwaterandcarbonResultsweresummarizedtoecologicalsubsectionsand(https://www.usanpn.org/).ClimatechangecancreateaprovidedfortheindividualRPAclimateprojectionsthatmismatchbetweenthetimespecificvegetation(food)isproducetheminimumandmaximumamountofchangebyavailableandthetimewhenconsumersareseekingthatearly-andmid-century(2020to2040and2041to2070,vegetation.Forexample,ifpollinatorssuchasbeesandrespectively),aswellasfortheensemblephenologicalbutterfliesarrivetoanareaaftervegetationflowering,response.TheclimateprojectionsthatproducetheminimumtherewouldbelittleopportunityforpollinationandseedandmaximumamountofchangeinSOSorEOSprovidedevelopment,therebythreateningfoodwebsandtheabilityinformationaboutthefullrangeofpotentialfuturechangeinofthespeciestoreproduce.Inthissectionweexplorerangelandgrowingseasons,whileensembleresultsprovideprojectedchangesinphenologyrepresentedbyalterationstheaverageprojectedchangeinvegetationphenology(basedinphenologicaltiming,whichwedefineasthetimefromonallfiveclimatemodelprojections).Climateprojectionstheonsetofgreennesstothecessationofgreenness(https://thatproduceminimumandmaximumchangewereselectedwww.usgs.gov/special-topics/remote-sensing-phenology).basedonresultsfortheentireextentofrangelandsacrossThisshouldnotbeconfusedwiththegrowingseasonlengththeconterminousUnitedStatesandarethereforenotassociatedwithplanthardinesszones,whichisdefinedbyalwaysrepresentativeoftheminimumsandmaximumsforthefrost-freeperiodandhasbeenincreasingacrossU.S.individualregions.rangelands(https://www.epa.gov/climate-indicators/climate-change-indicators-length-growing-season).Whileincreasingfrost-freeperiodscouldtheoreticallyresultinlongergrowingseasons,wefoundthatcriticalnutrientssuchaswaterandnitrogenwerenotsufficientlyabundanttosupportextendedgrowingseasons,andthatlimitationsintheavailabilityofthesenutrientsactuallyleadtoshortergrowingseasonsacrossU.S.rangelands.2020ResourcesPlanningActAssessment8-19StartofSeasonTable8-12.Projectedchangesinstartofseason(SOS)andendofseason(EOS)phenology(Juliandays)forearlycentury(2020to2040)andGrowingseasonsareprojectedtobothstartandendearliermid-century(2041to2070),comparedwiththebaselineperiodof2000tointhefuture,andtheseshiftsareprojectedtointensifyover2014.Theensembleresultprovidestheaverageamountofchangethatistime,withSOSstartingevenearlierinmid-centurythanprojectednationallyandforeachregionacrossallfiveclimateprojections.earlycentury(table8-12).ComparedwiththebaselineTheleastwarmclimateprojectionproducestheminimumamountofperiod,thegrowingseasonwasprojectedtostart4to5changeinSOSunderRCP4.5and8.5.ThewetandhotclimateprojectionsdaysearlieronaverageacrossallthreeregionsforearlyproducethemaximumamountofchangeinSOSunderRCP4.5andRCPcentury(2020to2040)underRCP4.5,whilethegrowing8.5,respectively.Theleastwarmandhotclimateprojectionsproducetheseasonformid-century(2041to2070)wasprojectedminimumandmaximumamountofchangeinEOS,respectively,underbothtostart6to8daysearlier(table8-12).ProjectedSOSRCPs4.5and8.5.ClimateprojectionsthatproduceminimumandmaximumgenerallyoccursearlierunderRCP8.5thanunderRCP4.5,changewereselectedbasedonresultsfortheentireextentofrangelandsinthealikelyresultoftheintensifiedradiativewarming,withtheconterminousUnitedStatesandarethereforenotalwaysrepresentativeoftheexceptionofSOSminimumchangeprojectedbytheleastminimumsandmaximumsforindividualregions.warmclimateprojection.RCP4.5RCP8.5ThePacificCoastRegionisprojectedtoseethelargestaverageearliershiftinSOS,followedbytheRockyPhenology2020to2041to2020to2041MountainandSouthRegions,howeverthepotentialexistsParameter204020702040to2070fortheRockyMountainRegiontoexperienceasimilarearlyshiftinSOS,shownbythemaximumSOSresult.LocalSOS(Ensemble)changeinJulianDayspatternsexhibitgreatervariabilityinmodeledphenologicalSOS(Max)changesthantheregionalpatternsdescribedabove.InSOS(Min)NationaladditiontogrowingseasonsstartingandendingearlierunderEOS(Ensemble)RCP8.5thanRCP4.5,thereisalsomorespatialvariabilityEOS(Max)-4.7-7.1-5.6-8.1intheamountofchangeexhibitedacrossU.S.rangelandsEOS(Min)underRCP8.5(figure8-16).Forbothearly-andmid-century-4.0-6.8-8.2-12.2underRCP4.5and8.5,theGreatBasin,easternWashingtonSOS(Ensemble)andOregon,andthesouthernreachesoftheColoradoSOS(Max)-5.6-7.2-2.8-4.1Plateau(especiallynearnortheasternArizona)showedtheSOS(Min)largestshifttoanearlierSOS(upto22days;figure8-16).EOS(Ensemble)-7.9-13.1-9.2-17.8EOS(Max)EndofSeasonEOS(Min)-8.3-14.2-11.6-23.8AswithSOS,theEOSisprojectedtooccurearlierintheSOS(Ensemble)-5.6-10.0-7.7-17.5future,moresounderRCP8.5thanRCP4.5duetotheSOS(Max)intensifiedradiativewarming.EOSisprojectedtoshiftmoreSOS(Min)SouthRegionthanSOS—forallregions,inbothtimeperiods,andunderEOS(Ensemble)bothRCPs—resultinginashorterannualgrowingseason.EOS(Max)-4.2-5.8-5.5-6.3ThegrowingseasonisprojectedtoseethelargestaverageEOS(Min)earliershiftinEOSintheSouthRegion,followedbythe-1.5-2.5-7.5-9.2PacificCoastandRockyMountainRegions(table8-12).SOS(Ensemble)Comparedwiththebaselineperiod,earlycenturyEOSSOS(Max)-3.9-6.6-3.6-3.6ensembleprojectionsunderRCP4.5rangedfrom6daysSOS(Min)earlyintheRockyMountainRegionto9daysearlyintheEOS(Ensemble)-9.4-16.5-11.3-22.9SouthRegion,increasingatmid-centuryto10and16daysEOS(Max)early,respectively(table8-12).AswithSOS,localpatternsEOS(Min)-12.8-21.3-14.6-31.1ofEOSexhibitgreatervariabilitythanintheregionalpatternsdescribedabove(figures8-16and8-17).TheEOS-4.6-9-7.9-20.8projectionsshowadifferentspatialpatternthanSOS,withthesouthernGreatPlains(principallyTexasandOklahoma)RockyMountainRegionprojectedtoexperiencethelargestchange,endingthegrowingseasonupto31daysearlierbymid-centuryunder-4.8-7.2-4.8-8.3RCP8.5(figure8-17).-5.2-8.9-7.8-13.2-6.4-7.5-1.9-3.5-6.5-10-6.9-13.8-7.9-13.8-9-18.8-4.2-4.9-5.9-13.6PacificCoastRegion-5.1-8.2-6-9.7-5.2-8.9-9.3-14.3-6.4-7.5-2.8-5.1-7.9-12.9-9.3-16.8-4.1-7.4-11.3-21.5-8.1-16-9.3-18.2EOS=endofseason;max=maximum;min=minimum;RCP=RepresentativeConcentrationPathway;SOS=startofseason.Source:Zimmeretal.2022.8-20FutureofAmerica’sForestsandRangelandsFigure8-16.Projectedensemblechangeinthestartofthegrowingseasoncomparedtoa2000to2014baselinefor(a)RCP4.5earlycentury,(b)RCP4.5mid-century,(c)RCP8.5earlycentury,and(d)RCP8.5mid-century.TheensembleresultprovidestheaverageamountofprojectedchangeacrossallfiveRPAclimateprojections.Pixel-levelphenologyprojectionswereaggregatedtoecologicalsubsections(BaileyandHogg1986).aRCP4.5EarlycenturybRCP4.5Mid-centurycRCP8.5EarlycenturydRCP8.5Mid-centuryRCP=RepresentativeConcentrationPathway.Source:Zimmeretal.2022.Figure8-17.Projectedensemblechangeintheendofthegrowingseasoncomparedtoa2000to2014baselinefor(a)RCP4.5earlycentury,(b)RCP4.5mid-century,(c)RCP8.5earlycentury,and(d)RCP8.5mid-century.TheensembleresultprovidestheaverageamountofprojectedchangeacrossallfiveRPAclimateprojections.Pixel-levelphenologyprojectionswereaggregatedtoecologicalsubsections(BaileyandHogg1986).aRCP4.5EarlycenturybRCP4.5Mid-centurycRCP8.5EarlycenturydRCP8.5Mid-centuryRCP=RepresentativeConcentrationPathway.Source:Zimmeretal.2022.2020ResourcesPlanningActAssessment8-21GrowingSeasonConsiderations❖ThenorthernGreatPlains,especiallyNorthDakota,RegardlessoftheRCPorclimateprojectionevaluated,SouthDakota,andMontana,areprojectedtoshortergrowingseasonsandanearlieronsetofgreenupwereexperiencethelargestgainsinproductivity.universallyprojected.WhileEOStiminghasoftenbeenoverlookedinphenologyresearch,ourfindingsconfirmitWedevelopedannualprojectionsofabovegroundNPPonmaybeasormoresignificantthanSOStiminginthefuture.rangelandsunderRCP4.5and8.5usingtheRPAclimateNationally,earlierEOSandSOSsuggestthepotentialforprojectionsandtheMC2dynamicglobalvegetationmodelgrowingseasonstobebetween3to4daysshorterbyearly(Bacheletetal.2015,Kimetal.2018)usinga2015to2019centuryand6to10daysshorterbymid-century.baselineduetodataavailability.Resultsweresummarizedtoecologicalsubsections(BaileyandHogg1986)andRPAProjectionsofRangelandProductivityregionsandprovidedfortheindividualclimateprojectionsthatproducetheminimumandmaximumNPPvaluesas❖ProductivitychangeswillhavemodesteffectsonwellastheensembleNPPresponse(theaverageNPPacrossallfiveRPAclimateprojections).Climateprojectionsthatthetotalnationalforagesupplyinthefuture,butproduceminimumandmaximumNPPprojectionswereimpactswillbesignificantregionallyandlocally.selectedbasedonresultsfortheentireextentofrangelandsacrosstheconterminousUnitedStatesandmaynotalways❖Projectionssuggestthatmanyofthetrendsthatberepresentativeoftheminimumsandmaximumsforindividualregions.havebeenobservedsince1984—includingdecreasedNPPintheSouth,increasedNPPinNPPisprojectedtoincreasewithincreasinglatitudeinalltheNorth,andgreaterinterannualvariability—willregionsrelativetothebaselinewhenexaminingtheensemblecontinueandpossiblyintensifyinthefuture.results,particularlyformid-centuryunderRCP8.5(figure8-18).NPPisprojectedtoincreaseovertimeinboththeNorth❖TheSouthwesternUnitedStatesisprojectedtoandRockyMountainRegionsfortheensembleresults,withthelargestgainsoccurringintheNorthandwithgainsforbothexperiencethelargestandmostwidespreadNPPreductions,especiallyindesertareas,followedbythesouthernplainsandFourCornersarea.Figure8-18.ProjectedensembleproportionalchangeinNPPcomparedtoa2015to2019baselinefor(a)RCP4.5earlycentury,(b)RCP4.5mid-century,(c)RCP8.5earlycentury,and(d)RCP8.5mid-century.TheensembleresultprovidestheaverageamountofprojectedproportionalchangeacrossallfiveRPAclimateprojections.aRCP4.5EarlycenturybRCP4.5Mid-centurycRCP8.5EarlycenturydRCP8.5Mid-centuryRCP=RepresentativeConcentrationPathway.Source:Kimetal.2018.8-22FutureofAmerica’sForestsandRangelandsregionsbeinglargerunderRCP8.5thanRCP4.5(table8-13;Theselargeregionalaverages,however,masknoteworthyfigure8-18).Thehotanddryclimateprojections,however,subregionalpatternsthatareevidentwhencomparingtheproduceNPPdeclinesfortheRockyMountainRegion,whileprojectedsmallestandlargestfutureoveralllevelsofNPPthedryclimateprojectionproducesNPPdeclinefortheNorth(figures8-19,8-20).ThenorthernGreatPlainstendtoRegionbymid-century(table8-13;figure8-19).TheSouthoutperformallotherareas,especiallyinNorthDakotaandRegionisprojectedtoexperiencedeclinesinNPPbytheeasternMontana,rangingfrommoderatelossesofNPPhot,dry,andensembleresults,butisprojectedtoexperience(figure8-19)tosubstantialgains(figure8-20).However,increasesinNPPbytheleastwarmclimateprojection(tabletheseincreasingNPPtrendscouldbepartlycausedby8-13;figures8-19,8-20).ResultsforthePacificCoastRegionexpandingshrubandotherwoodyspeciescover(KlemmetarethemostvariablebetweenRCPs,withthelargestNPPal.2020).ProductivityisprojectedtodecreasebyasmuchdeclinesofanyregionprojectedunderRCP4.5overallas31percentundertheworst-casescenarioinmuchofthetimescales,andincreasesinNPPprojectedbyallclimatedesertSouthwestandsouthernplains,especiallyKansas,projectionsandunderRCP8.5atlevelsmeetingorexceedingOklahoma,andeasternColorado,withsimilarlossesinUtahthoseprojectedfortheRockyMountainRegion(table8-13;andsouthernCalifornia(figure8-19).Althoughtheextentfigures8-18,8-19,8-20).ofseveredeclinesisreducedunderthebest-casescenario,theseareasarestillunderhighrisk(figure8-20).TheleastTable8-13.ProjectedproportionalchangesinNPPforearlycentury(2020warmclimateprojectionproducedthehighestoverallNPPto2040)andmid-century(2041to2070),comparedwiththebaselineperiodprojections;however,thedesertSouthwestisstillprojectedof2015to2019.Theensembleresultprovidestheaverageamountofchangetoexperiencedeclinesfrom5to25percentbymid-century,thatisprojectednationallyandforeachregionacrossallfiveRPAclimatedependingonthelocality.projections.ThehotanddryclimateprojectionsproducetheminimumNPPvaluesunderRCP4.5and8.5,respectively.TheleastwarmclimateprojectionIncreasingtemperaturesthroughouttheentireprojectionproducesthemaximumNPPvaluesunderRCP4.5and8.5.ClimateperiodarelikelyresponsiblefordrivingpatternsinmostprojectionsthatproduceminimumandmaximumNPPvalueswereselectedregions(Reevesetal.2014a);however,someoffsettingisbasedonresultsfortheentireextentofrangelandsintheconterminousUnitedpossibleasincreasingCO2concentrationsmayalsoincreaseStatesandarethereforenotalwaysrepresentativeoftheminimumsandsoilmoistureviareducedevapotranspiration,especiallyinmaximumsforindividualregions.thepresenceofwarmseasonspecies(C4photosyntheticpathway)(Morganetal.2011).WhileincreasedRCP4.5RCP8.5temperaturesareexpectedacrossmostregions,variableprojectedprecipitationpatternsandtrendscreatemostNPPParameter2020to2041to2020to2041toofthesubregionaldifferencesinNPPandforagequality(Augustineetal.2018).NPP(Ensemble)2040207020402070NPP(Max)NPP(Min)percentNPP(Ensemble)NationalNPP(Max)NPP(Min)-1.53.03.06.5NPP(Ensemble)2.310.58.022.0NPP(Max)NPP(Min)-7.8-2.53.0-6.3NPP(Ensemble)NorthRegionNPP(Max)NPP(Min)410511NPP(Ensemble)7271736NPP(Max)NPP(Min)314-7SouthRegion-4-2-2-218713-8-3-9-23RockyMountainRegion044739620-9-29-2PacificCoastRegion-60510-2-2219-17-687Max=maximum;Min=minimum;NPP=netprimaryproductivity;RCP=RepresentativeConcentrationPathway.Source:Kimetal.(2018).2020ResourcesPlanningActAssessment8-23Figure8-19.ProjectedproportionalchangeinNPPfromthe2015to2019baselinerepresentingthelowestNPPprojections(NPPmin)for(a)RCP4.5earlycentury,(b)RCP4.5mid-century,(c)RCP8.5earlycentury,and(d)RCP8.5mid-century.ThehotclimateprojectionproducedthelowestoverallNPPprojectionsunderRCP4.5,whilethedryclimateprojectionproducedthelowestNPPprojectionsunderRCP8.5.aRCP4.5EarlycenturybRCP4.5Mid-centurycRCP8.5EarlycenturydRCP8.5Mid-centuryNPP=netprimaryproductivity;RCP=RepresentativeConcentrationPathway.Source:Kimetal.2018.Figure8-20.ProjectedproportionalchangeinNPPfromthe2015to2019baselinerepresentingthehighestNPPprojections(NPPmax)for(a)RCP4.5earlycentury,(b)RCP4.5mid-century,(c)RCP8.5earlycentury,and(d)RCP8.5mid-century.TheleastwarmclimateprojectionproducedthehighestoverallNPPprojectionsunderbothRCPs.aRCP4.5EarlycenturybRCP4.5Mid-centurycRCP8.5EarlycenturydRCP8.5Mid-centuryNPP=netprimaryproductivity;RCP=RepresentativeConcentrationPathway.Source:Kimetal.2018.8-24FutureofAmerica’sForestsandRangelandsLandUseProjectionsWeprovideresultsandinterpretationfocusedonestimatedchangesinrangelandsbyRPAregionandcounties❖RangelandlossesareexpectedtobeminorunderRCPs4.5and8.5fortheearly-andmid-centuryperiods,althoughitisimportanttonotethatthelandusenationally,decreasing2.7percenttoabaseofprojectionsareinfluencedbyeconomicfactors(intheform257millionhabymid-century,butregionalandofSharedSocioeconomicPathway,SSP)inadditiontolocalimpactswillbesignificant.RCPandclimate.WhiletherearenotmanydifferencesinthenationalresultsbetweenRCPs4.5and8.5,thereare❖ThePacificCoastRegionisprojectedtolosenotabledifferencesamongRPAregionsandbetweentheearlycenturyandmid-centuryperiods.Weagainprovidethemostrangelandarea,about6percentunderresultsfortheindividualclimateprojectionsthatproducebothRCPs,butsomecountieswithinthatregiontheminimumandmaximumamountofpercentagechangemayloseupto25percentoftheirrangelandsinrangelandarea,aswellasfortheensembleresponsetourbanization.(theaverageprojectedchangeinrangelandareaacrossallfiveclimateprojections).Theminimumandmaximum❖SomegainsinrangelandareaareprojectedselectionswereagainbasedonanalysisfortheentireextentofrangelandsacrosstheconterminousUnitedStatesandwhereagriculturallandusedecreases,maythereforenotalwaysrepresenttheminimumsandparticularlyinNevada.maximumsforindividualregions.TheNorthRegionwasnotincludedinthisanalysisbecauserangelandsarenotLanduseprojectionsandtheassociatedmethodologyareprojectedintheNorthRegionbyBrooksetal.(2020).discussedintheLandResourcesChapter,aswellasinMissouriistheonlyStateintheNorthRegionwhereMihiarandLewis(2019)andBrooksetal.(2020).OurrangelandsaremonitoredbytheNRIAssessment(USDAcalculationsofchangestotherangelandlandbasedifferNRCS2018)duetothescarcityofrangelandsinthefromcalculationsintheLandResourcesChapter.Here,NortheasternUnitedStates;thelackofavailablemonitoringwecalculatetheaveragechangeinprojectedrangelanddatarestrictstheabilitytomakeprojections.areaacrosstheearlycenturyperiod(2020to2040)andmid-centuryperiod(2041to2070)tocompareagainsttheAllregionsareprojectedtoloserangelandsinthefuture,andobservedNRI2012baselinerangelandlandbase.Thistheselossesareprojectedtoincreasefromearly-tomid-methodincorporatesfluctuationstotherangelandlandbasecentury(table8-14).ResultsfrombothRCPsaresimilar,asthatoccurovertheearly-andmid-centurytimeperiodsareresultsacrossthedifferentclimateprojections.TheSouthandmakescomparisonsagainstobservedvalues.TheLandRegionexhibitstheslowestrateofrangelandlossunderallResourcesChapter,however,comparesprojectedrangelandclimateprojections,scenarios,andtimeperiods(rangelandareaintheyears2040and2070(notaveraged)againstaprojected2020baseline,thuseliminatinginterannualvariabilityintherangelandlandbaseandconfiningresultstothe2020to2070RPAprojectionperiod.Table8-14.Projectedpercentchangeinrangelandlanduseforearlycentury(2020to2040)andmid-century(2041to2070),comparedwiththe2012baselineunderRCPs4.5and8.5.Datarepresentthechangeinlanduseasapercentageofthebaseline.TheensembleresultprovidestheaverageamountofchangethatisprojectednationallyandforeachregionacrossallfiveRPAclimateprojections.ThewetandhotclimateprojectionsproducetheminimumchangeunderRCPs4.5and8.5,respectively.ThedryclimateprojectionproducesthemaximumchangeunderRCPs4.5and8.5.ClimateprojectionsthatproduceminimumandmaximumchangewereselectedbasedonresultsfortheentireextentofrangelandsacrosstheconterminousUnitedStatesandarethereforenotalwaysrepresentativeoftheminimumsandmaximumsforindividualregions.RPAregionMinimum2020to2040(%)MaximumRCP4.5Minimum2041to2070(%)MaximumNational-1.1-1.1RCP8.5-3.3-3.5South-0.4Ensemble-0.4-1.3Ensemble-1.3RockyMountain-0.5-1.1-0.5-1.4-3.4-1.5PacificCoast-2.3-0.4-2.4-7.2-1.3-7.7-0.5-1.5National-0.9-2.4-1.2-2.3-7.4-3.7-0.5-0.9-1.4South-0.4-1.1-0.5-1.2-3.2-1.6-0.4-2.5-4.9-1.3-8.1RockyMountain-0.4-0.5-1.4-2.3-7PacificCoast-1.8RCP=RepresentativeConcentrationPathway.Sources:MihiarandLewis2019;Brooksetal.2020.2020ResourcesPlanningActAssessment8-25lossesareneverprojectedtoexceed1.5percent),whiletheClara(-17percent),andStanislaus(-13percent).Wyoming,PacificCoastRegionexhibitsthefastestrateofrangelandsoutheasternOregon,andnorthernArizonaarealsoloss,ashighas8.1percentbymid-centuryunderRCP8.5projectedtolosesubstantialamountsofrangelandrelative(table8-14).tootherareas.Reevesetal.(2018)demonstratedhowlargeurbangrowthrateshavebeenobservedandareprojectedtoThesenationalandregionaltrendsobscuresubregionalcontinueinthenearfutureinhotspotsaroundtheWestsuchpatternsofchangeinrangelandarea(figure8-21).UnderasBozeman,MT;Boise,ID;andPhoenix,AZ.RCP8.5,ensembleresultsprojectthat63countieswillloseatleast1percentoftheirrangelandbaseintheearlycenturyIncontrast,Nevadaappearstoincreaseinrangelandareainperiod,with7countiesinCaliforniaprojectedtoexhibitseveralcounties,especiallyWhitePineandNye.Rangelandsinlossesgreaterthan3percent.Bymid-century,326countiesWhitePineCountyareprojectedtoincreasebyupto6percentwereprojectedtoloseatleast1percentoftheirrangelandunderRCP8.5.Causesfortheincreasedrangelandareaarebase(orbetween296and343countiesintheminimumandunclearbutthesedatasuggestthattheclimateinthoseareasmaximumresults,respectively),with61countiesprojectedwilllikelybecomeunsuitableforagriculture,andabandonedtoexhibitlossesexceeding3percent(63countiesinthecroplandswilltransitiontorangelands.Abandonedcroplandmaximumchangeresults).ThreecountiesinCaliforniaweretypicallybecomesweedy,however,andtheusefulnessoftheseprojectedtoexhibitlossesexceeding10percentoftheirlandsisthereforelikelylowfromarangelandhealthperspectiverangelandbasebymid-centuryunderRCP8.5,primarilytoorfromahabitatperspectiveforwildlifespeciesthatdependonurbanexpansion,includingRiverside(-21percent),Santaproperlyfunctioningrangelands.Figure8-21.Projectedchangeinrangelandareacomparedwiththe2012baselineastheensembleofresultsacrossthefiveRPAclimateprojectionsfor(a)RCP4.5earlycentury,(b)RCP4.5mid-century,(c)RCP8.5earlycentury,and(d)RCP8.5mid-century.aRCP4.5EarlycenturybRCP4.5Mid-centurycRCP8.5EarlycenturydRCP8.5Mid-centuryRCP=RepresentativeConcentrationPathway.Source:MihiarandLewis2019;Brooksetal.2020.ManagementImplicationsspecies,asymmetricandincreasinglyvariableNPPinsomeregions,andshortergrowingseasonsthatbothstartandendThisRPArangelandassessmentidentifiedcurrentandfutureearlierintheyear.Theincreasingfrequencyofdroughtandtrendsonrangelandsthatmaypresentongoingchallengestowildfiresonrangelands(seetheDisturbanceChapter)couldmanagers,producers,andpolicymakers.Managerswilllikelyexacerbatetheseimpacts.GiventhetrendsandprojectedbefacingbothdecreasingrangelandareaandhealthinthefuturesdocumentedinthisAssessment,managersandfuture,asthechangingclimateresultsinincreasinginvasive8-26FutureofAmerica’sForestsandRangelandspolicymakerswilllikelyfaceincreasinglydifficultchoicesSecond,rangelandsareexperiencingarangeofdisturbances,basedontradeoffs.Maintainingflexibilityinthemanagementsomeofwhicharechangingecosystemdynamicsinofpubliclandgrazingleasesandreconsideringandupdatingunprecedentedways,includinginvasivespecies,wildfires,annualoperatinginstructions(USDAForestService1997)anddrought.Rangelandsareexhibitingincreasesininvasivemorefrequentlyaschangingconditionsareidentifiedinnewannualherbaceousspecies(e.g.,cheatgrassandredbrome)datastreams(e.g.,availabilityofremotelysensedrangeland)andwoodyspeciesofconcern(e.g.,mesquiteandjuniper);canhelpmanagersadjusttochangingconditions.Managersthesetrendsarevisibleindatafromallevaluatedplot-mayneedtoconsidersocialfactorsmoreconsistentlythanlevelrangelandmonitoringprograms(NRIonnon-Federalinthepastandmaybenefitfromwideningtheircircleoflands,AIMonBLMlands,andFIAACIonUSDAForeststakeholderstoaddressissuesthatincreasinglydemandcross-Servicelands)aswellasthroughremotesensing.Increasesdisciplineandcross-boundarysolutions(Reedetal.2009).ininvasiveannualherbaceousspeciesinfluencefireregimesandcreatecontinuingfeedbackcycles.TheamountofareaLandmanagershavenewtoolsandresourcesavailable,burnedinrangelandshasnearlydoubledsince2000(seethesuchastheClimateChangeAdaptationLibrary(http://DisturbanceChapter),causedinlargepartbytheincreasingadaptationpartners.org/library.php),asearchabledatabaseprevalenceanddensityofinvasiveannualherbaceousspecies.thatcontainsideasforincreasingecologicalresiliencyforallThesechanges,combinedwithincreasingdroughtintensitylandsincludingrangelands.Similarly,the2021Rangelandandfrequency(seetheDisturbanceChapter),arecreatingTechnologySummit(https://vimeo.com/showcase/8429328/h)increasedinterannualvariabilityofforagewithimpactstobroughttogetheranddiscussedmorethan30technologiesrangelandhealth.Importantly,thecombinationofincreasingthatrangemanagerscanusetoenhancemonitoring-informeddroughtandpresenceofinvasiveannualgrassesreducesadaptivemanagementandprofessionaldevelopment.Usingresiliencytodrought(Chambersetal.2014).ProlongednewtoolsandimprovedcommunicationstylescanhelpdroughtsintheSouthwesternUnitedStatesandCaliforniamanagersquantifyandcopewiththeincreasedvariabilityarecreatingnovelconditionsthathavenotbeenexperiencedoccurringonU.S.rangelands.sincewellbeforeEuro-Americansettlement(Szejneretal.2021).TheseconditionsareexpectedtooccurwithConclusionsgreaterfrequencyinthefuture,creatingecological,social,andeconomicchallenges.ThesedisturbancesarealreadyInthisRPArangelandassessment,weassembledtheavailablenegativelyaffectingsocialfabricsandeconomicpatternsnationallyconsistentdatatoexaminetheconditionsandaroundrangelandsintheconterminousUnitedStates(MaczcotrendsofrangelandsintheconterminousUnitedStates,etal.2022),andprojectedfuturedisturbancesmayexacerbatealongwiththeimpactsofclimatechange.Technologicalexistingstressorssuchasreducedincomesfromrangelands,advancementsincomputerprocessingpowerandremotelyfewerrecreationalopportunities(e.g.,greaterrestrictionsonsenseddata,combinedwithnewsamplingprogramsfromthepubliclandwhenwildfireriskisextreme),andhighercostsforBLM(AIM)andtheUSDAForestService(ACI),enabledredmeat.TheseplausibleoutcomessuggesttheneedfornovelenhancedanalysesoverpastRPAAssessments.Theinauguralwaysofcommunicatingaboutandrespondingtodisturbance,assessmentofvegetationtrendsacrossalllandsusingwithanemphasisonadaptationtoprepareforpotentiallymoreremotelysenseddatafrom1984to2020corroboratedfindingssevereconditionsinthefuture.fromboththeNRIandAIMprocesses.Wealsodevelopedprojectionsofphenology,NPP,andlanduseacrossplausibleThird,thepastandcurrenttrendsdocumentedherearefutureclimatesthatcanbeusedbytheUSDAForestServiceprojectedtocontinueatleastthroughthemid-centuryperiod.andthebroaderrangemanagementcommunitytoaddressThestartandendofthevegetationgrowingseasonarebothpolicyandmanagementneeds.projectedtocontinuetoshiftearlierthroughtime,withtheendshiftingmorethanthestartresultinginshorterperiodsofplantThroughtheseanalyses,weidentifiedthreesignificantgrowthoverall.Atthesametime,NPPdeclinesareprojectedfindingsforU.S.rangelands.First,theU.S.rangelandbasetocontinueinsouthernrangelands,alongwithcontinuedhasbeendecreasingatarateofabout161,874ha(399,000increasesininterannualvariability.AlthoughNPPincreasesacres)peryearsince1982,withthemostsignificantlossesareprojectedinmanynorthernrangelands,thisislikelyresultingfromtransitionstourbanandagriculturallanduses.attributabletoincreasingannualgrasspresence.Inaddition,Futurelossesareexpectedtoremainrelativelyconstantatrangelandareaisprojectedtocontinuetodeclineastheresultabout98,101ha(242,412acres)peryear,totalingadditionalofconversiontourbanlanduse,withthelargestdeclineslossesofaround4.7millionha(11,613,935acres)by2070.projectedforthePacificCoastRegion.TheprojectedWhilethisisasmallpercentageofthetotalrangelandbase,continuationofthetrendsidentifiedinthisassessmenttheserangelandlosseshavespatiallyexplicitramifications,suggestecologicalchallengestothesustainabilityofgoodsincludingincreasingdifficultyassociatedwithmaintainingandservicesprovidedbyU.S.rangelands.criticalhabitatandcorridorsforwildlifeandgeneticdiversity.2020ResourcesPlanningActAssessment8-27AnalogProjectionsTranslatingclimatemodelprojectionsintointuitiveAgricultureandFoodSecurity(http://www.ccafs-climate.assessmentsforthepublicisamajorchallengefortheorg/).FourEarthsystemmodels,whicharesimilartothescientificcommunity.Climate-analogmappinginvolvesclimatemodelsselectedfortheRPAAssessment,werematchingtheexpectedfutureclimateatalocation(suchusedtoestimateclimatefuturesunderRCPs4.5and8.5:asacityornationalforest)withthecurrentclimateofMOHC-HadGEM2-ES(similartoRPAhotmodel),MRI-adifferentlocation.Thismethodprovidesarelatable,CGCM3(similartoRPAleastwarmmodel),IPSL-CM5A-place-basedassessmentofpotentialimpactsofclimateMR(similartoRPAdrymodel),andNCC-NorESM1-Mchange.Herewedemonstrateaclimateanaloganalysis(similartoRPAmiddlemodel).toprovideasenseofthemagnitudeofprojectedclimatechangeforcitiesinregionsdominatedbyrangelandsWefocusedonagroupof65citiessurroundedby(FitzpatrickandDunn2019).Futureclimateforthe2080srangelands,primarilyintheWesternUnitedStates,and(30-yearrunningmeanoftheperiod2070to2099)wereperformedclimate-analogmapping(FitzpatrickandobtainedfromtheConsultativeGroupforInternationalDunn2019,Mahonyetal.2017,Williamsetal.2007)AgriculturalResearchprogramonClimateChange,(figures8-22,8-23).Averagedacrossthe65citiesand4Figure8-22.Vectorsshowthedistanceanddirectionfromeachcity(filledcircles)tothelocationofthebestcontemporaryclimaticanalogforthatcity’sprojected2080climateunderRCP4.5fortheseclimateprojections:(a)MRI-CGCM3(similartoRPAleast-warmmodel),(b)IPSL-CM5A-MR(similartoRPAdrymodel),(c)NCC-NorESM1-M(similartotheRPAmiddlemodel),and(d)MOHC-HadGEM2-ES(similartotheRPAhotmodel).(a)MRI-CGCM3(b)IPSL-CM5A-MR(c)NCC-NorESM1-M(d)MOHC-HadGEM2-ESSource:FitzpatrickandDunn2019.8-28FutureofAmerica’sForestsandRangelandsclimatemodels,annualmeantemperaturewasprojectedtocitiesagainsttheclimatenormalsforHelenaallowsforincreasebynearly5°C,withthelargestseasonalincreasessomegeneralizations.First,averagehightemperatureintemperatureexpectedinthesummerandautumnunderinJulyincreasesfrom28to33°C.Second,theaverageRCP8.5.AverageannualprecipitationwasprojectedtoJanuaryminimumtemperatureincreasesfrom-11to-5declineby6percent,withseasonalprecipitationprojected°C.Theseincreasesintemperaturehaveanegativeeffecttodecreasebyatleast10percentinallseasonsexceptonsnowfall,projectedtodeclineby300mm(about12winter,wherea15-percentincreasewasprojected.inches),whichwilllikelynegativelyimpactskiingandAveragingacrosscitiesobscuresimportantregionalotherwinterrecreationactivities.Precipitationisexpectedvariation.Forexample,citiesintheSouthwestweretostaynearnormalorincrease,buttheeffectivenessoftheprojectedtoexperiencedeclinesinannualprecipitation,rainfalltoimprovehydrologicconditions(fillreservoirs,whereascitiesinthePacificNorthwest,northernGreatkeepstreamsrunningwithcold-enoughwatertoprotectPlains,andportionsofCaliforniawereprojectedtoendangeredbulltrout,etc.)decreasesduetosignificantlyexperienceincreasesinprecipitation.However,someofhighertemperatures.Thedecreaseineffectiveprecipitationthesesameregionswerealsoexpectedtoexperiencethewilllikelyalterbothnativeanddomesticvegetationlargesttemperatureincreases,whichcouldoffsetincreasesassemblages;forexample,theclimateinLapwaiisinprecipitationthroughreductionsinsoilmoisture.presentlysuitableforvineyards,whilecurrentlygrowingtomatoesinHelenaisdifficult.Toaidcomprehensionoftheresults,weprovidecasestudiesforHelena,MT,andDenver,CO.Table8-15AnalogconditionsforDenversuggestthatitsclimateshowscurrentclimateattributesofHelenaandDenver,willcometoresemblecurrentconditionsinTyrone,OK;alongwiththecurrentclimateattributesforthecitiesthatClarendon,TX;Plains,TX;orSeminole,TX.Theseserveasthebestanalogduringthelatecenturyperiodanalogcitiesoccurat954mabovesealevel,onaverage,(30-yearrunningmeanoftheperiod2070to2099).ThewhileDenveris1,609mabovesealevel;theseanaloganalogssuggestthatHelena’sclimatewillbecomemostcitiesrepresenta40-percentdecreaseinelevation,andlikeSt.Ignatius,MT;Lapwai,ID;Kooskia,ID;orSaltclimateexpectationsvarysignificantlywitha650-mLakeCity,UT.Comparingtheclimatesoftheseanalogchangeinelevation.TheaverageoftheanalogcitiesTable8-15.ResultsoftheclimateanaloganalysisforRCP8.5.ThecurrentclimateattributesofHelena,MT,andDenver,CO,areshown,alongwiththecurrentclimateattributesforthecitiesthatserveasthebestanalogduringthelatecenturyperiod(30-yearrunningmeanoftheperiod2070to2099).CityClimateMRI-IPSL-CM5A-MRNCC-MOHC-AveragechangerelativenormalCGCM3NorESM1-MHadGEM2-EStopresentdayDenver,CO1,948-2,005Tyrone,OKClarendon,TXSeminole,TXElevation(m)1,609823Plains,TX-655AverageJulyhigh890351,0971,0063temperature(°C)3133AverageJanuarylow3434temperature(°C)-3Rainfall(mm)-8-7-4457-24Snowfall(mm)40661076951,524483127Kooskia,ID457-1,321Helena,MT1,938-2,016432Lapwai,ID3931781,181Saint29033SaltLakeCity,-469Elevation(m)28Ignatius,MT34UT5AverageJulyhigh884-41,280temperature(°C)635AverageJanuarylow2966034temperature(°C)Rainfall(mm)-11-8-4-66Snowfall(mm)3054064324061651,2701,1185591,524-305m=meters;mm=millimeters;RCP=RepresentativeConcentrationPathway.Source:FitzpatrickandDunn2019.2020ResourcesPlanningActAssessment8-29suggeststhattemperaturesinDenverwillincreaseinbothdependentonwinteractivities.SomeoftheimpactcouldJulyandJanuaryby3and4°C,respectively.ThemostbebufferedathigherelevationareaswhereskiingisadramaticchangeexpectedinDenverisasharpdecreasemajoreconomicdriver—suchasinTelluride,CO,whichinsnowpack.Presently,Denverreceivesabout1,524mmhasrelativelyhigh-elevationskiruns(topat4,010m)—ofsnowfallannually,andanalogconditionssuggestahowever,lesssnowoverallwilllikelyincreasecompetitionlossofnearly1,300mm.Thisdecreaseinsnowfallhasfortheseresources,creatingmorecrowdedsituations.thepotentialtosubstantiallydisruptlocaleconomiesFigure8-23.Vectorsshowthedistanceanddirectionfromeachcity(filledcircles)tothelocationofthebestcontemporaryclimaticanalogforthatcity’sprojected2080climateunderRCP8.5fortheseclimateprojections:(a)MRI-CGCM3(similartoRPAleast-warmmodel),(b)IPSL-CM5A-MR(similartoRPAdrymodel),(c)NCC-NorESM1-M(similartotheRPAmiddlemodel),and(d)MOHC-HadGEM2-ES(similartotheRPAhotmodel).(a)MRI-CGCM3(b)IPSL-CM5A-MR(c)NCC-NorESM1-M(d)MOHC-HadGEM2-ESSource:FitzpatrickandDunn2019.8-30FutureofAmerica’sForestsandRangelandsLiteratureCitedChambers,J.C.;Roundy,B.A.;Blank,R.R.;Meyer,S.E.;Whattaker,A.2007.WhatmakesGreatBasinsagebrushecosystemsinvasiblebyAlford,E.;Vivanco,J.;Paschke,M.2009.TheeffectsofflavonoidBromustectorum?EcologicalMonographs.77(1):117–145.allelochemicalsfromknapweedsonlegume-rhizobiacandidatesforrestoration.RestorationEcology.17(4):506–514.Chen,X.;Weifeng,P.2002.Relationshipsamongphenologicalgrowingseason,time-integratedNormalizedDifferenceVegetationAllen,B.H.1988.Forestrangelandrelationships.In:Tueller,P.T.eds.IndexandclimateforcinginthetemperateregionofEasternChina.Vegetationscienceapplicationsforrangelandanalysisandmanagement.InternationalJournalofClimatology.22(14):1781–1792.https://doi.Handbookofvegetationscience,vol14.Dordrecht:Springer:339–362.org/10.1002/joc.823.https://doi.org/10.1007/978-94-009-3085-8_14.Coates,P.S.;Prochazka,B.G.;Ricca,M.A.;Gustafson,K.B.;Ziegler,P.;Ansley,R.;Huddle,J.;Kramp.,B.1997.Mesquiteecology.TexasCasazza,M.L.2017.PinyonandjuniperencroachmentintosagebrushNaturalResourcesServer.http://texnat.tamu.edu/library/symposia/ecosystemsimpactsdistributionandsurvivalofgreatersage-grouse.brush-sculptors-innovations-for-tailoring-brushy-rangelands-to-enhance-RangelandEcologyandManagement.70(1):25–38.wildlife-habitat-and-recreational-value/mesquite-ecology/.DiTomaso,J.2000.Invasiveweedsinrangelands:species,impacts,andAugustine,D.;Blumenthal,D.;Springer,T.;LeCain,D.R.;Gunter,S.A.;management.WeedScience.48(2):255–265.Derner,J.D.2018.ElevatedCO2inducessubstantialandpersistentdeclinesinforagequalityirrespectiveofwarminginmixedgrassprairie.Fitzpatrick,M.C.;Dunn,R.R.2019.ContemporaryclimaticanalogsEcologicalApplications.28(3):721–735.for540NorthAmericanurbanareasinthelate21stcentury.NatureCommunications.10:art.614.AugustineD.;Davidson,A.;Dickinson,L.;vanPelt,B.2021.Thinkinglikeagrassland:challengesandopportunitiesforbiodiversityFox,W.E.;McCollum,D.W.;Mitchell,J.E.;Swanson,L.E.;Kreuter,conservationintheGreatPlainsofNorthAmerica.RangelandEcologyU.P.;Tanaka,J.A.;Evans,G.R.;Heintz,H.T.;Breckenridge,R.P.;&Management.78:281–295.Geissler,P.H.2009.AnIntegratedSocial,Economic,andEcologicConceptual(ISEEC)frameworkforconsideringrangelandsustainability.Bachelet,D.;Ferschweiler,K.;Sheehan,T.J.;Sleeter,B.M.;Zhu,Z.SocietyandNaturalResources.22(7):593–606.2015.ProjectedcarbonstocksintheconterminousUSAwithlanduseandvariablefireregimes.GlobalChangeBiology.21(12):4548–4560.Frame,D.J.;Rosier,S.M.;Noy,I.;Harrington,L.J.;Carey-Smith,T.;https://doi.org/10.1111/gcb.13048.Sparrow,S.N.;Stone,D.A.;Dean,S.M.2020.Climatechangeattributionandtheeconomiccostsofextremeweatherevents:astudyondamagesBailey,R.;Hogg,H.1986.Aworldecoregionsmapforresourcefromextremerainfallanddrought.ClimaticChange.162:781–797.reporting.EnvironmentalConservation.13:195–202.Gaines,E.M.;Campbell,R.S.;Braisington,J.J.1954.ForageproductionBakker,K.K.;Higgins,K.F.2009.PlantedgrasslandsandnativesodonlongleafpinelandsinsouthernAlabama.Ecology.35:59–62.prairie:equivalenthabitatforgrasslandbirds?WesternNorthAmericanNaturalist.69:235–242.Gu,Y.;Brown,J.F.;Miura,T.;vanLeeuwen,W.J.D.;Reed,B.C.2010.PhenologicalclassificationoftheUnitedStates:ageographicframeworkBalch,J.K.;Bradley,B.A.;D'Antonio,C.M.;Dans,J.G.forextendingmulti-sensortime-seriesdata.RemoteSensing.2:526–544.2013.IntroducedannualgrassincreasesregionalfireactivityacrossthearidwesternUSA(1980–2009).GlobalChangeBiology.19:173–Hall,M.1996.AgronomyFacts50KentuckyBluegrass.Pennsylvania183.https://doi.org/10.1111/gcb.12046.StateUniversity,CollegeofAgriculturalSciences,PennStateCooperativeExtension.http://extension.psu.edu/plants/crops/forages/Brooks,E.B.;Coulston,J.W.;Riitters,K.H.;Wear,D.N.2020.Usingaspecies/kentucky-bluegrass.(20July2020).hybriddemand-allocationalgorithmtoenabledistributionalanalysisoflandusechangepatterns.PLoSONE.15(10):e0240097.Herrick,J.E.;VanZee,J.W.;McCord,S.E.;Courtright,E.M.;Karl,J.W.;Burkett,L.M.2017.Monitoringmanualforgrassland,shrubland,andBrooks,M.L.;D'Antonio,C.M.;Richardson,D.M.;Grace,J.B.;Keeley,savannaecosystems.Vol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arch2022).JournalofAgricultural,BiologicalandEnvironmentalStatistics.25:250–275.https://doi.org/10.1007/s13253-020-00392-5.USDAForestService(USDAForestService).2020.LandareasoftheNationalForestSystem.U.S.DepartmentofAgriculture,ForestService.Zimmer,S.N;Reeves,M.C.;St.Peter,J.;Hanberry,B.B.2022.Earlierhttps://www.fs.usda.gov/land/staff/lar-index.shtml.(8September2021).green-upandsenescenceoftemperateUnitedStatesrangelandsunderfutureclimate.ModelingEarthSystemsandEnvironment.8:5389–USDANationalAgriculturalStatisticsSurvey(NASS).2021.https://5405.www.nass.usda.gov/.(8September2021).Authors:RogerClaassen,USDANaturalResourcesConservationServiceEmilyKachergis,U.S.DepartmentoftheInterior,BureauofMattReeves,USDAForestService,RockyMountainResearchStationLandManagementMichaelKrebs,ConsultingEcologistLorettaJ.Metz,USDANaturalResourcesConservationServiceSarahE.McCord,USDAAgriculturalResearchServiceBriceB.Hanberry,USDAForestService,RockyMountainMattFitzpatrick,UniversityofMarylandCenterforResearchStationEnvironmentalScience2020ResourcesPlanningActAssessment8-33Chapter9WaterResourcesWarziniack,Travis;Arabi,Mazdak;Froemke,Pamela;Ghosh,Rohini;Heidari,Hadi;Rasmussen,Shaundra;Swartzentruber,Ryan.2023.WaterResources.In:U.S.DepartmentofAgriculture,ForestService.2023.FutureofAmerica’sForestandRangelands:ForestService2020ResourcesPlanningActAssessment.Gen.Tech.Rep.WO-102.Washington,DC:9-1–9-20.Chapter9.https://doi.org/10.2737/WO-GTR-102-Chap9.Inthischapter,weexaminetrendsinfreshwateruseandAmongthemostencouragingtrendsinwaterresourcesissupplythroughouttheconterminousUnitedStatesandthetremendousgainsinwateruseefficiency.WateruseintheirimplicationsforfutureshortagesduetosocioeconomictheUnitedStatesdecreased9percentbetween2010andandclimatechange.Wefocusonrenewablefreshwater,2015,making2015thelowestlevelofwaterusesincewhichincludessurfaceandsubsurfaceflows,andprovidebefore1970(Dieteretal.2018).Thisdecreasecamedespiteprojectionsoffreshwatersupplyandlikelihoodofwaterpopulationincreases,inpartduetoefficiencygainsinshortageunderfuturescenarios.Regardingthesourcesofhouseholdappliances,thermoelectricpowergeneration,andwatersupply,wefoundthat39percentofallwaterwithinirrigatedagriculture,alongwithstructuralchangeswithintheconterminousUnitedStatesoriginatesonforestedlands.theU.S.economythathavefavoredlesswater-intensivePercentagesarehigherintheEasternUnitedStates,whereserviceindustriesovertraditionalmanufacturing(Dieteretforestsmakeupalargershareofthelandbase.Relativeal.2018,WangandHejazi2011).BothpercapitawaterusesharesofwaterfromforestsarelowerintheWesternUnitedandtotalwaterusehavedeclinedthroughoutthecountry.States,butthepercentagethatcomesfromnationalforestsFromhouseholdstoagriculturetoindustry,meaningfulismuchhigher,highlightingtheneedtomanagepublicandchangeshaveoccurredinhumanbehaviorandconservationprivateforestsforsustainablewaterresources.practices.Nonetheless,largeregionsoftheUnitedStatesKeyFindings❖Bothpercapitawateruseandtotalwaterusearedeclininginmanypartsofthecountry.❖Despitereductionsinwateruse,manyregionsincreasinglyexperiencewatershortagesduetoextendeddryperiods.❖Projectedchangesinnationalconsumptivewateruserangefroma9-percentdecreasetoa235-percentincrease,withthelargestimpactsresultingfromtheneedsofagricultureinresponsetoclimatechange.❖Changesinprojectedaggregatewateryieldbymid-centuryrangefroma25.7-percentincreaseunderawetfuturetoa10.9-percentdecreaseunderadryfuture.❖Short-durationdroughtsarelikelytoturnintolong-durationdroughts,andtheintensityofdroughtislikelytoincreasesubstantially.Underhigherfutureatmosphericwarming,droughtslastingmorethanayearareprojectedtooccurfourtimesmoreoftenandincreaseinintensityby76percent.❖Adaptationoptionslikeincreasedreservoirstoragehavelimitedabilitytocurtailshortageinthelongterm.Responsestoclimatechangewillprobablyrequiresubstantialtransfersfromagriculturetourbanusers,whichcouldhaveseriousnegativeimpactsonruralcommunities.2020ResourcesPlanningActAssessment9-1faceincreasingwaterscarcity.DroughtsareincreasingupdatedwithmethodsanddetailedresultsinWarziniackinfrequencyandduration,andthereisahighamountofetal.(2022).Futureprojectionsaredevelopedforthefouruncertaintyinfuturedroughtcharacteristics.WhethercoreRPAscenariosandfiveclimatemodels(seethesidebarthesetrendscontinuedependsonfuturepopulationgrowth,RPAScenarios).Thoughnotspecificallycoveredinthissector-specificratesoftechnologyadaptation,andcontinuedAssessment,muchofthiswatercomesdirectlyfromforestedchangesinregionalclimaticpatterns.Climatemodelsdifferlands.Roughly60millionpeopledependonforestsformoreintheirprojectedfutureprecipitationpatterns,moresothanthan50percentoftheirwatersupply(Liuetal.2021).forprojectionsoftemperature.RegionsthatfacedecreasingwatersupplyandeitherhavelargeamountsofwateruseforProjectionsofwateruserelyonthreemaincomponents:aagricultureorhavehighpopulationgrowthareprojectedtoprincipaldriver,aper-unitrateofwithdrawal,andclimatefaceincreasingshortagesthroughthemiddleofthecentury.feedbacks(table9-1).Principaldrivers(suchaspopulationThesecompoundingeffectsofclimateandsocioeconomicoracresofirrigatedagriculture)arefirstmultipliedbytheforceswilllikelychallengepolicymakersandforcetoughper-unitrateofwithdrawal(suchaspercapitawithdrawalsdecisionsaboutwateruseamongsectors.fordomesticuse)togettotalfreshwaterwithdrawalsabsentclimatechangeeffects.RatesofwithdrawalsinsomesectorsTrendsinFreshwaterarethenadjustedtoincludeclimateimpactsonwateruseWithdrawals:PastandProjectedefficiency,theneedformorewaterinawarmerclimate,andchangesinwateruseduetochangesinprecipitation.Climate❖MostregionsoftheUnitedStatesareexpectedfeedbacksonlyaffecttheper-unitratesofwithdrawalsanddonotaddresstheviabilityoflandtosupportagiventoseedeclinesoronlymodestincreasesinwateruse(e.g.,viabilityofagriculture)ortemperaturelimitsonwithdrawalsforhouseholduse.specificuses(e.g.,temperaturelimitationsonwithdrawingwaterforthermoelectricitygeneration).❖WarmertemperaturesduetoclimatechangeareTable9-1.Principaldrivers,ratesofwithdrawals,andclimatefeedbacksusedprojectedtoincreasewateruseintheenergyinwateruseprojections.sectorby20to60percent(1to6billiongallonsofwaterperday)—morethanwouldbeneededSectorPrincipalWithdrawalClimateimpactswithoutclimatechange.driverrateDomesticChangesinsummertime❖TotalwithdrawalsforirrigatedagricultureinthePopulationGallonsperprecipitationandThermoelectriccapitaevapotranspirationconterminousUnitedStatesareprojectedtoPopulation,impacthouseholdincreasefrom116billiongallonsin2015to134IrrigatedtotalGallonsperoutdoorwaterusebilliongallonsin2070underahotfuture.agriculturethermoelectricIndustrialandelectricitykWhproducedChangesintemperature❖TotalconsumptiveuseisprojectedtodecreasemininguseusingfreshwaterleadtochangesinLivestockandbyasmuchas9percentnationallyunderaaquacultureAcresGallonsperacrehouseholdandindustriallowerwarmingandmoderatepopulationgrowthirrigatedenergydemandfuturebutincreaseby235percentunderahighGallonsperwarmingandhighpopulationgrowthfuture,PersonaldollarincomeChangesingrowingindicatingahighlevelofvariationinpotentialincomeGallonsperseasonprecipitationleadfuturesandcreatingchallengesformanagersPopulationtocorrespondingchangeshopingtoadapttoclimatechange.personinirrigationdemandThissectionoftheResourcesPlanningAct(RPA)NoclimateimpactsinAssessmentexaminestrendsinpastwaterwithdrawalsandmakesprojectionsforfuturewithdrawalsforthemodelconterminousUnitedStates,drawingheavilyoncounty-Noclimateimpactsinleveldatafromthe5-yearU.S.GeologicalSurvey(USGS)waterusecircularsforwhich2015isthemostrecentdatamodelyear(Dieteretal.2018).Detailisgivenherefordomestic,industrial,irrigatedagriculture,andthermoelectricpowergenerationsectors.Togetherthesefoursectorsmakeup72percentoftotalwaterwithdrawalsinthecountry(Dieteretal.2018).ProjectionsofwithdrawalsextendtrendsintheUSGSdatafollowingBrownetal.(2013),whichare9-2FutureofAmerica’sForestsandRangelandsRPAScenariosTheRPAAssessmentusesasetofscenariosofcoordinatedFigure9-1.Characterizationofthe2020RPAAssessmentfutureclimate,population,andsocioeconomicchangetoscenariosintermsoffuturechangesinatmosphericwarmingandprojectresourceavailabilityandconditionoverthenext50U.S.socioeconomicgrowth.Thesecharacteristicsareassociatedyears.ThesescenariosprovideaframeworkforobjectivelywiththefourunderlyingRepresentativeConcentrationPathwayevaluatingaplausiblerangeoffutureresourceoutcomes.(RCP)–SharedSocioeconomicPathway(SSP)combinations.The2020RPAAssessmentdrawsfromtheglobalSource:Langneretal.2020.scenariosdevelopedbytheIntergovernmentalPanelonClimateChangetoexaminethe2020to2070time(table9-2);however,characteristicscanvaryatfinerperiod(IPCC2014).TheRPAscenariospairtwospatialscales.Althoughthesamemodelswereselectedalternativeclimatefutures(RepresentativeConcentrationtodevelopclimateprojectionsforbothlowerandhigh-PathwaysorRCPs)withfouralternativesocioeconomicwarmingfutures,therearedistinctclimateprojectionsforfutures(SharedSocioeconomicPathwaysorSSPs)ineachmodelassociatedwithRCP4.5andRCP8.5.Thethefollowingcombinations:RCP4.5andSSP1(lowerScenariosChapterdescribeshowtheseclimatemodelswarming-moderateU.S.growth,LM),RCP8.5andSSP3wereselected;JoyceandCoulson(2020)giveamore(highwarming-lowU.S.growth,HL),RCP8.5andSSP2extensiveexplanation.(highwarming-moderateU.S.growth,HM),andRCPThroughouttheRPAAssessment,individualscenario-8.5andSSP5(highwarming-highU.S.growth,HH)climatefuturesarereferredtobypairingRPAscenarioswith(figure9-1).Thefour2020RPAAssessmentscenariosselectedclimateprojections.Forexample,ananalysisrunencompasstheprojectedrangeofclimatechangefromunder“HL-wet”assumesafuturewithhighatmospherictheRCPsandprojectedquantitativeandqualitativewarmingandlowU.S.populationandeconomicgrowthrangeofsocioeconomicchangefromtheSSPs,resulting(HLRPAscenario),aswellasawetterclimatefortheinfourdistinctfuturesthatvaryacrossamultitudeofconterminousUnitedStates(wetclimateprojection).characteristics(figure9-2),andprovidingaunifyingframeworkthatorganizestheRPAAssessmentnaturalresourcesectoranalysesaroundaconsistentsetofpossibleworldviews.TheScenariosChapterdescribeshowthesescenarioswereselectedandpaired;moredetailsareprovidedinLangneretal.(2020).The2020RPAAssessmentpairsthesefourRPAscenarioswithfivedifferentclimatemodelsthatcapturethewiderangeofprojectedfuturetemperatureandprecipitationacrosstheconterminousUnitedStates.Anensembleclimateprojectionthataveragesacrossthemultiplemodelprojectionsisnotusedbecauseoftheimportanceofpreservingindividualmodelvariabilityforresourcemodelingefforts.ThefiveclimatemodelsselectedbyRPArepresentleastwarm,hot,dry,wet,andmiddle-of-the-roadclimatefuturesfortheconterminousUnitedStatesTable9-2.Fiveclimatemodelsselectedtoreflecttherangeofthefullsetof20availableclimatemodelsintheyear2070.EachmodelwasrununderRCP4.5andRCP8.5,providingarangeofdifferentU.S.climateprojections.LeastwarmHotDryWetMiddleIPSL-CM5A-MRNorESM1-MClimatemodelMRI-CGCM3HadGEM2-ESCNRM-CM5InstitutPierreSimonNorwegianClimateInstitutionMeteorologicalMetOfficeHadleyLaplace,FranceNationalCentreofCenter,NorwayResearchCentre,UnitedMeteorologicalResearch,KingdomInstitute,JapanFranceSource:JoyceandCoulson2020.2020ResourcesPlanningActAssessment9-3Figure9-2.Characteristicsdifferentiatingthe2020RPAAssessmentscenarios.ThesecharacteristicsareassociatedwiththefourunderlyingRepresentativeConcentrationPathway(RCP)–SharedSocioeconomicPathway(SSP)combinations.PastWaterWithdrawalspercentnationallydespitean8-percentincreaseinpopulation.Percapitahouseholdwithdrawalsfellfrom98gallonsperdayDifferencesinwaterwithdrawalsthroughouttheUnitedin2005to82gallonsperdayin2015.IrrigationwithdrawalsStates(figures9-3,9-4)existduetohistoricaldifferencesfellby7percent,andthermoelectricwithdrawalsfellby34inwaterabundance,patternsofsettlement,agriculturalpercent(Dieteretal.2018).expansion,andindustrialdevelopment.Agricultureisthelargestuserofwaterinmostplaces,accountingfor42Someofthosereductionsinwaterusewerenecessaryduepercentoffreshwaterwithdrawalsnationally,andislikelytoextremedroughtsthroughoutthelast2decades.InJulytobethedrivingfactorinfuturewatershortages(Dieteret2021,LakeMead,thelargestreservoirintheUnitedStates,al.2018,WarziniackandBrown2019).Manycropsrequirerecordeditslowestwaterlevelssinceitwasfilled(BOR20to30inchesofwaterperyear;areaswithprecipitation2021).Somereductions,however,havecomebywayofbelowthatamounthavetorelyonirrigationtosuccessfullyremarkableimprovementsinwaterusetechnology,includingfarm(Postel1998).Waterforirrigationdominatesallotherimprovementsinirrigationsmethods,increaseduseoflow-usesintheseareas,leadingtovisualdifferencesinfigureflowtoilets(thelargestin-homeuseofwater),increaseduse9-3.Comparatively,waterwithdrawntoproduceelectricityofhigh-efficiencyshowerheadsandfaucets,incentivestorepresents34percentofnationalfreshwaterwithdrawals,reduceoutdoorwateruse,andgovernmentpolicies(Gleicketandhouseholdwaterusemakesup9percentoffreshwateral.2009,Leeetal.2013,MillockandNauges2010).TheU.S.withdrawals.economycontinuestobecomelesswater-intensive,asseenbymeasureslikegrossdomesticproductpergallonsofwateruseBetween2005and2015,surfacefreshwaterwithdrawalsthathavebeenfallingfordecades(Dieteretal.2018,Wangdecreasedin64percentofcountiesintheconterminousUnitedandHejazi2011).Statestoabout322billiongallonsperday(figure9-3d).Duringthattime,domesticwithdrawalsforhouseholdusefellby109-4FutureofAmerica’sForestsandRangelandsFigure9-3.Freshwaterwithdrawals(surfaceandgroundwaterandshareofsurface)in2015andaspercentchangefrom2005to2015.(a)TotalSurfaceandGroundwaterWithdrawals(b)PercentChangeinSurfaceandintheUnitedStatesperDayin2015GroundwaterWithdrawals,2005to2015≤15≤-100≤45≤-25≤60≤0≤80≤100≤100101+(c)ShareofSurfaceWithdrawalsin2015(d)PercentChangeinSurfaceWithdrawals,2005to2015Source:Dieteretal.2018.Figure9-4.Waterwithdrawals(surfaceandgroundwater)foreachsectorbyStatein2015.Statesareorderedfromwesttoeast,lefttoright.25,00020,00015,00010,0005,0000DomesticIndustrialThermoelectricLivestockandAquacultureIrrigationSource:Warziniacketal.2022,basedondatafromDieteretal.2018.2020ResourcesPlanningActAssessment9-5ProjectionsofWaterWithdrawalsDomesticWaterWithdrawalsProjectionsforfreshwaterwithdrawalsaredescribedbrieflyDomesticwaterwithdrawalsarecalculatedasthehereforthedomestic,industrial,andirrigatedagricultureproductofcountypopulationprojectionsandpercapitasectors.Projectionsforthermoelectricpowergenerationarewithdrawals,adjustedforimpactsonoutdoorwaterusedueforconsumptiveuseinsteadofwithdrawals,makinguseoftoclimatechange.WearandPrestemon(2019)estimatenewdatafromUSGS.Warziniacketal.(2022)providemorethatU.S.populationwillincreaseby24to44percentunderdetailedmethodsaswellasprojectionsforallUSGSwatermoderate-growthSSPsandby56percentunderthehigh-usesectorsoutto2070.TheanalysisisdoneatthecountygrowthSSP5.ThefastestgrowingregionsareexpectedscalefortheconterminousUnitedStatesandaggregatedtotobeintheWestandSouthwest,whicharealreadyfacingRPAsubregions(seefigure2-1intheIntroductionChapter).waterstress(U.S.GlobalChangeResearchProgram2018)Totalwaterwithdrawalswere322billiongallonsperdayinandprojectedtoseepopulationsdoubleunderthehigh-2015,ofwhich198billiongallonsperdaywerefromfreshgrowthSSP5.surfacewatersources.By2070,weestimatewithdrawalsintheconterminousUnitedStateswillrangefroma10-percentDespitetheseincreases,mostregionsoftheUnitedStatesreductionunderHL-wet(thehighatmosphericwarmingareexpectedtoseedeclinesoronlymodestincreasesinandlowsocioeconomicchangeRPAscenariousingthewetdomesticwaterwithdrawalsassociatedwithlow-andclimateprojection)toanover200-percentincreaseundermoderate-growthscenarios(figures9-5,9-6).In2015,totalHH-hot.AcrossallRPAscenario-climatefutures,thereisawithdrawalsfordomesticusewere26.6billiongallonsmeanincreaseof47percentintotalwithdrawals.perday,ofwhich23.3billiongallonsperdaycamefromFigure9-5.Current(2015)andprojectedfuture(2070)domesticwithdrawalsbyRPAsubregionandRPAscenarioforthefiveRPAclimateprojections.MilliongallonsperdayMilliongallonsperdayMilliongallonsperdayMilliongallonsperdayMilliongallonsperdayCURRENTLMHLHMHHLM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.9-6FutureofAmerica’sForestsandRangelandsFigure9-6.Meanpercentchangefromcurrent(2015)toprojectedfutureFigure9-7.Current(2015)andfuture(2070)industrialwithdrawalsby(2070)indomesticwaterwithdrawalsacrossallRPAscenario-climatefutures.RPAsubregion.ProjectionsforindustrialwithdrawalsdonothaveclimatefeedbackssoonlyvarybySSP.IndustrialwaterwithdrawalsMilliongallonsperday≤0≤0.1≤0.4≤0.9≤2.5publicsuppliersand3.3billiongallonsperdaywereself-CURRENTSSP1SSP2SSP3SSP5supplied,largelythroughwells.Self-suppliedsurfacewaterwithdrawalswereonly49milliongallonsperdayin2015.SSP=SharedSocioeconomicPathway.In2070,withdrawalsfordomesticuseintheconterminousUnitedStatesareprojectedtorangefrom22billiongallonsBecauseprojectionsforindustrialwithdrawalsdonotperdayto50billiongallonsperday.Inthesouthernandhaveclimatefeedbacks,resultsaremodeledonlyusingwesternpartsofthecountry,rapidpopulationgrowthissocioeconomicpathwaysandnotusingtheintegratedRPAexpectedtooutpaceimprovementsinwateruseefficiency,scenariosorclimatemodels.Allregionsareprojectedtoleadingtoincreasesinwithdrawalsfordomesticuseinthoseseedeclinesinindustrialwithdrawalsforlow-growthSSP3regionsacrossallsocioeconomicfutures.Underhigh-growthandmodestincreasesundermoderate-growthSSPs1andHH-middle,allbut10countiesacrosstheUnitedStates2.Allregionsareprojectedtoseeincreasesinindustrialareprojectedtoseeincreasesindomesticwithdrawals,withdrawalsunderhigh-growthSSP5,withnoticeablecomparedtothelow-growthHL,forwhich78percentincreasesintheNorthCentralandSouthCentralSubregionsofcountiesareprojectedtoseedecreasesindomesticduetotheinitialsizeofindustry.withdrawals.Becausepopulationistheprimarydriverfordomesticdemands,SSPstendtoimpactprojectionsmoreThermoelectricWaterUsethanatmosphericwarmingandclimatemodelselection.Theexceptionisthedryclimateprojection,particularlyforThermoelectricpowergeneration,whichrepresentsthetheSouthCentralSubregion,whichshowsamuchlargerlargestsegmentofU.S.electricityproduction,requireswaterareaofdryingcenteredonTexasandspreadingthroughoutatseveraldifferentpointsinthelifecycleofthegenerationthesubregion.Undertheseconditions,increasesinoutdoorprocess,includingcomponentmanufacturing,fuelacquisition,waterusedrivelargeincreasesintotaldomesticwithdrawals.processingandtransport,andpowerplantoperationanddecommissioning,butwaterisprimarilyusedforcoolingIndustrialWaterWithdrawalspurposes(Meldrumetal.2013).Totalwaterwithdrawalsforpowergenerationpeakedin2010,andwateruserates(unitsofTheindustrialsectorisprimarilymadeupoflargeusersofwaterwithdrawnperunitofelectricityproduced,ingallons/self-suppliedwater.Thus,differencesinfigure9-7reflectkilowatthour)havefallenfrom22.41in1985toaslowasregionaldifferencesinwateravailabilityasmuchastheydo10.76in2015duetolargeradoptionofrecirculatingcoolingregionaldifferencesineconomicactivity.Waterwithdrawalstechnologiesallowingforgreaterefficiencyinwateruse.intheindustrialsectorrangefromnearzerointhePacificSouthwesttohighamountsofwithdrawalsinthecentralEstimationofelectricitydemandforfreshwaterregions,reflectingregionaldifferencesinmanufacturingthermoelectricplantsiscomplicatedbythefactthatactivityandhowfirmsusewater(Dieteretal.2018).Fortheelectricityconsumedinonebasinmaybeproducedinmostpart,gainsinwaterefficiencyandshiftsintheeconomyanother.Asecondcomplicationarisesbecauseelectricitytowardlesswater-intensiveindustriesleadtodeclinesinindustrialwaterwithdrawalsacrossthecountry.2020ResourcesPlanningActAssessment9-7isproducedatnotonlyfreshwaterthermoelectricplantsTheU.S.EnergyInformationAdministrationprojectsbutalsoatsaltwaterthermoelectric,hydroelectric,solar,energyconsumptiontoincrease0.3percentforeverywind,andothertypesofplants.Forprojectingfutureuse1.9-percentincreaseinU.S.output(U.S.EnergyInformationoffreshwateratthermoelectricplants,weestimategrowthAdministration2020),leadingtoincreasesinenergyuseofinthermoelectricproductionforlargeenergyregionsof150percentby2070formoderate-socioeconomicgrowththeUnitedStates,subtracttheportionoftheproductiontoscenarios(SSP1andSSP2)andover400percentforhigh-beproducedatnon-freshwaterthermoelectricplants,andsocioeconomicgrowthscenarios(SSP5).Theseincreasesinapportiontheremainingproductiontoeachcountywithinelectricityproductionleadtoincreasesinwaterconsumptionrespectiveregions.fromjustunder2.5billiongallonsofwaterperdayin2015tobetween5and17billiongallonsperdayin2070(figure9-8).OurapproachutilizesrecentlyreleasedUSGSupdatedestimatesofthermoelectricwaterusein2015(DiehlandBy2070,increasingtemperaturesduetoclimatechangeHarris2014,2019).ThenewUSGSmethodcategorizesareprojectedtorequire20to60percentmorewaterforthermoelectricplantsintheUnitedStatesthatwithdrawelectricityproductionthanwouldbeneededwithoutwaterbasedontheirmethodsofgeneratingelectricityclimatechange.Thatincreaseisequivalenttoanextra1anddisposingofwasteheat.TheUSGSdataincludeto6billiongallonsofwaterperdayneededduetoclimateconsumptiveuseattheplantlevel,whichwemakeuseofchange.Theseprojectionsassumeacontinuationofpasthere.Insteadofreportingwithdrawalsandthenconvertingtrendsinwateruseefficiencybutdonotaccountforlargethemtoconsumptiveusebasedonregionalaverages,thissuddenshiftsduetochangesinpolicy,newtechnologies,sectionreportsconsumptiveusedirectly.orfueltypes.TheyalsodonotaccountforincreasingwaterFigure9-8.Current(2015)andfuture(2070)thermoelectricconsumptiveusebyRPAsubregionandRPAscenarioforthefiveRPAclimateprojections.MilliongallonsperdayMilliongallonsperdayMilliongallonsperdayMilliongallonsperdayMilliongallonsperdayCURRENTLMHLHMHHLM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.9-8FutureofAmerica’sForestsandRangelandstemperaturesthatmightimpedecoolingatthermoelectriccontinuealongpasttrends,asdoestheamountofwaterpowerplants(VanVlietetal.2012).appliedtoanaverageacreineachregion.ClimateimpactsareintroducedthroughchangesincropwateruseduetoIrrigatedAgricultureWithdrawalschangesinevapotranspiration;theydonotincludechangesincroptypeorgrowingseasonsthatmightresultduetoAgricultureisthelargestuserofwaternationally,accountingwarmertemperatures(Woznickietal.2015).for42percentoftotalfreshwaterwithdrawals.IndryregionslikeCalifornia,agriculturecanmakeupmorethanUnderthehotclimateprojection,whichrepresentsaworst-80percentoftotalwithdrawals.Significantamountsofcasescenarioformanyoftheagriculturalregions,totalwaterwaterarealsousedforagriculturethroughoutthesoutherndemandedforirrigationintheUnitedStatesisprojectedMississippiRiverbasin(figure9-9).In2015,the17Westerntoincreasefrom116billiongallonsperdayin2015to134Statesaccountedfor91percentoftotalsurfacewaterbilliongallonsperdayin2070(figure9-10).Thehotclimateirrigationwithdrawals(Dieteretal.2018).projectionissignificantlydrierthancurrentconditionsinthePacificSouthwestandIntermountainWestSubregions,bothPreviouswatershortagesandcompetitionfromurbanofwhichrelyonlargeamountsofirrigationforagriculture.useshaveledtodecreasesinsurfacewateruseintheWestEstimatesforagriculturalwithdrawalsdonotconsiderthroughreductionsintheamountoflandirrigated,amountchangesinpopulationorincomebutdoincludethechangesofwaterappliedonanypieceofland,andshiftsfromsurfaceinRCPs4.5(lowerfuturewarming)and8.5(higherfuturetogroundwatersupplies.Between1985and2015,irrigationwarming),aswellaschangesinamountofirrigatedacreage.depthonanaverageacreintheWestfellbyanannualizedSSPswithhighpopulationgrowtharelikelytodecreasetherateof0.85percent.IntheEast,however,agriculturalwateramountofagriculturalacreagefasterthanhistoricallyseenusehasincreasedasfarmersuseirrigationtooffsetimpactsandthatareprojectedhere.Insuchcases,highpopulationofmorevariedprecipitationandseekmorereliableyields.growthmightdecreaseagriculturalwateruseifitcausesThisanalysisassumesratesofchangeinirrigatedacresconversionofcroplandstodevelopment.Figure9-9.Agriculturalfreshwaterwithdrawals.WithdrawalsperAcreofIrrigatedCroplandWithdrawalAmountsperDayWithdrawals(milliongallonsperday)≤50≤200≤500≤1,000≤1,850Source:2015USGSestimates(Dieteretal.2018).2020ResourcesPlanningActAssessment9-9Figure9-10.Current(2015)andfuture(2070)agriculturalwithdrawalsbyRPAsubregionbyclimaticpathway(RCP)forthefiveRPAclimateprojections.Notethechangeinscaleforthehotclimateprojection.MilliongallonsperdayMilliongallonsperdayMilliongallonsperdayMilliongallonsperdayMilliongallonsperdayCURRENTRCP4.5RCP8.5RCP=RepresentativeConcentrationPathway.ProjectionsofConsumptiveUsetrendsinnationalwateruse(figure9-11).UnderHH-hot,consumptiveuseisprojectedtoincreaseby235percent.TheMuchofthewaterwithdrawnforhumanuseisreturnedtoGreatPlainsSubregionseesdecreasingconsumptivewaterusetheriverbasinfromwhichitcameintheformofrunoffandforallbutthedryclimateprojection,andtheIntermountainsewagedischarge.Theportionnotreturned,andthusnotSubregionshowsdecreasingconsumptivewateruseforallavailablefordownstreamuses,iscalledconsumptiveuse.Thebutthehotanddryclimateprojections.ThePacificNorthwestUSGSestimatedconsumptiveuseforirrigatedagricultureseesdeclinesinconsumptiveuseunder9outofthe20andthermoelectricpowergenerationin2015butonlyreportsscenario-climatefutures,andforallscenariosusingthedrywithdrawalsforothersectors.Nationally,about62percentclimateprojection,whichisactuallywetfortheregion(seeofwaterwithdrawnforagricultureisconsumptivelyused,theScenariosChaptersidebarUsingScenariosandProjectionscomparedto3percentofwaterwithdrawnforpowergenerationinResourceManagementPlanning).ThePacificSouthwest,(Deiteretal.2018).ConsumptiveuseforsectorsnotincludedinwhichseesvariationinfutureprecipitationpatternsbetweenUSGSestimatesrelyonolderUSGSestimates,datingbacktoclimateprojectionsandbetweennorthernandsouthernpartsof1990and1995inmanycases,andaugmentedwithvaluesfromthesubregion,seesdeclinesfor6outofthe20models.Largetheliteraturewhenpossible.Forthosesectors,consumptiveuseincreasesareprojectedfortheNorthCentral,SouthCentral,andratiosaretakenfromBrownetal.(2013).SoutheastSubregions,andtoalesserextentintheNortheast.TheseregionsareconsistentlyprojectedtoseeincreasesinTotalconsumptiveuseisprojectedtofallbyabout9percentconsumptiveuseacrossallsectorsoftheeconomy.underLM-middleandLM-hot,continuingpastdownward9-10FutureofAmerica’sForestsandRangelandsBecauseagricultureisthedominantuseofwaterinmostefficiencyhavemostlykeptupwithincreasesinpopulation.regions,resultsoftenvarybyclimateprojectionmorethanConsumptiveuseintheagriculturalsectorishighlyvariable,byRPAscenario.ManyregionsseeconsumptiveusemorewithdecreasesonaverageintheGreatPlainsandIntermountainthandoubleundertheclimateprojectionsthatyieldthedriestSubregions.Thelargestpercentageincreasesareprojectedconditionsfortherespectiveregions.Themostalarminginthermoelectricpowergeneration.AdaptationincoolingprojectionsacrossallmodelsandscenariosarefortheSouthtechnologieshaveledtoimprovementsinthesector,butforCentralSubregion,whichseesconsumptiveuserisebythisanalysis,populationandeconomicgrowthoutpacehistoricover300percentunderthedryclimateprojection.Theseratesofchange.Theseresultscouldbeinterpretedafewways.consumptiveuseprojectionsreflectoutcomesifcurrenttrendsTrendsintheanalysisreflecttrendsinpercapitaenergyuseandinwaterusecontinue.Inmanycases,suchoutcomesarenotwaterusedforanaveragekilowattofenergyproduced;thesefeasibleduetolimitedwatersupplyandhighlightareasinestimatesmaymisssuddenshiftsintechnology.However,whichlargereductionsmaybeneeded.thelargestincreasesinwateruseforthethermoelectricgenerationsectorareprojectedforthecentralregionsofFigure9-12showsprojectedchangesinconsumptiveusebytheUnitedStates.Theseregionsdrivemuchofthenationalsector.Inmostregions,projectedchangesinconsumptiveuseresultsandhavenotseenaswidespreadadoptionofmoreinthedomesticsectorarerelativelymodest.Gainsinwateruseefficientcoolingtechnologies.Figure9-11.ChangeintotalconsumptiveusebyRPAsubregionandRPAscenarioforthefiveRPAclimateprojections.Notethechangeinscaleforthehotclimateprojection.PercentchangePercentchangePercentchangePercentchangePercentchangeLMHLHMHHLM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.2020ResourcesPlanningActAssessment9-11Figure9-12.MeanchangesinconsumptiveusebysectorandRPAsubregionfrom2015to2070,acrossallscenario-climatefutures.DomesticIndustrialThermoelectricAquaculture&LivestockAgricultureTrendsinWaterYield:section,yieldisdifferentiatedfromsupply,whichisusedPastandProjectedinthenextsectiononstorage.Wateryieldisafunctionofprecipitationandevapotranspirationwithinawatershed.❖ChangesinwateryieldacrosstheconterminousWatersupplyincludeswateryieldaswellasincreasesanddecreasesduetowaterdiversionsbetweenwatersheds.UnitedStatesrangefroma25.7-percentincreaseunderawetfuturetoa10.9-percentdecreaseThecurrentRPAstudyimprovesonspatialandtemporalunderadryfuture.scalescomparedtopastRPAwaterassessments.ItutilizesanenhancedversionoftheVICmodelthatresolves❖Themostconsistentresultsacrossclimatefutureshydrologicalprocessesatthe4-x4-kmgridresolutionanddailytimestepstoprojectwateryieldandevapotranspirationareincreasesinprecipitationandyieldformuchbasedonbias-correctedanddownscaledregionaloftheWesternUnitedStates,decreasesintheclimateinputs.TheanalysisalsoincorporatesimprovedSouthwest,anddecreasesintheSouth.parameterizationofvariousmodelcomponentsforriverbasinsacrosstheconterminousUnitedStates(Nazetal.❖ManyEasternStatesreceivemorethan502016,Oubeidillahetal.2014).Hydrologicalresponsesaresubsequentlyaggregatedatthe8-digithydrologicunitcodepercentoftheirwaterfromforestedlands.(HUC8)watershedscaleforwatershortageassessmentsWesternStatesreceivesmallersharesof(Heidarietal.2021).Wateryieldfromforestedlands,waterfromforests,butwhatwaterdoescomeincludingnationalforests,isshownbyStateinthesidebarfromforestsoverwhelminglycomesfromWaterYieldfromForests.nationalforests.Current(1986to2015)dailyprecipitationandtemperatureHydrologicalresponsestoclimatevariabilityandchangearederivedfromDaymet(Thorntonetal.1997)andPRISMwereassessedforthecurrent(1986to2015)andmid-(Dalyetal.2008)datasets.TheNorthAmericanRegionalcentury(2041to2070)periods.TheVariableInfiltrationReanalysis(NARR)dataset(Mesingeretal.2006)isusedtoCapacity(VIC)model(Liangetal.1994)wasusedtoobtainhistoricalwind-speeddata.Futureclimateconditionssimulatehydrologicalresponses.Themodelisamacroscalearecharacterizedacrosspathwaysofclimaticchangesemi-distributedhydrologicalmodelthatsimulatesland-associatedwithatmosphericwarming(RCPs4.5and8.5),atmospherefluxesandwaterandenergybalancesattheusingthefiveclimatemodelsdescribedinthesidebarRPAlandsurface(CherkauerandLettenmaier2003).WateryieldScenarios(table9-1),selectedtospanleastwarm,hot,dry,representsdischargeatthewatershedoutletandincludeswet,andmiddleclimateconditionsacrosstheconterminousbothsurfacerunoffandgroundwatercontributions.RiverUnitedStates.Theseclimateprojectionsareusedtostorageandroutingarenotincludedinthemodel.Inthis9-12FutureofAmerica’sForestsandRangelandsWaterYieldfromForestsForestsplayanimportantroleintheprovisionofwater,WhetherforestscancontinuetoprovidereliablewaterbothbecausetheyprovidehighpercentagesofmanyinafuturewithclimatechangeisanimportantresearchStates’totalwateryieldandbecausethewaterfromforestsquestion.Nationalforestsandgrasslandsarelikelytoisgenerallymorereliableandofhigherqualitythanforexperiencelargerchangesinhydroclimaticconditionsotherlanduses(Ellisonetal.2017,Liuetal.2021).comparedtotheotherlandswithintheconterminousFigure9-13showspercentofwateryieldfromforestedUnitedStates(Heidarietal.2021).Underthehighlandsbasedoncurrentconditionsusedinthisassessment.atmosphericwarmingpathwayandthedry,middle,andAcrosstheconterminousUnitedStates,39percentofwetclimateprojections,nationalforestsinmountainouswateroriginatesfromforests,and15percentoriginatesregionsarelikelytohavelargerchangesinwateryieldfromnationalforestsandgrasslands.ManyEasternStatesandotherhydroclimaticconditionsthanotherregions.receivemorethan50percentoftheirwaterfromforestedAmongU.S.DepartmentofAgriculture,ForestServicelands.WestVirginiagetsabout80percentofitswatermanagementregions,theSouthwesternRegionisfromforests,followedbyNewHampshireandVermontlikelytoexperiencethelargestshiftsinwateryieldandwith74and70percent,respectively.WesternStateshydroclimaticcharacteristics.TheSouthernRegionisreceivesmallersharesofwaterfromforests,butwhatlikelytobecomemorearidwithsignificantdecreasesinwaterdoescomefromforestsoverwhelminglycomesfromwateryieldunderthedryclimateprojection.ThePacificnationalforests.Idahogets44percentofitswaterfromSouthwestandIntermountainRegionsarelikelytobecomenationalforests,alargerpercentagethananyotherState.lessaridandseeincreasesinwateryield.WateryieldfromColoradoandMontanaget32and30percentoftheirwaternationalforestsinthePacificNorthwestislikelytodeclinefromnationalforests,respectively.underallclimateprojectionsdespitetheprojectedincreaseinprecipitation.Figure9-13.PercentofwateryieldineachStatefromforestsandnationalforests,orderedfromwesttoeast.assessshiftsinhydrologicalresponsesandhydroclimaticwateryieldacrosstheconterminousUnitedStatesrangeconditions.Landuseisrepresentedbyhistoricalconditionsfroma25.7-percentincreaseunderthewetclimateandisheldconstantovertheassessmentperiod.projectiontoa10.9-percentdecreaseunderthedryclimateprojection.Figures9-15,9-16,and9-17showchangesPrecipitation,WaterYield,andPotentialinthespatialpatternsofprecipitation,wateryield,andEvapotranspirationpotentialevapotranspiration(PET)underthefiveselectedclimateprojectionsandtwopathwaysofclimaticchangeIngeneral,precipitationishigherintheEasternUnitedformid-century(2041to2070).TheprojectionsshowhighStates,leadingtohigherwateryield,whilepotentialvariability.IntheSouth,Southeast,andGreatPlains,thedryevapotranspirationishigherintheSouthwesternUnitedclimateprojectionshowsdecreasesinwateryield,whereasStates(figure9-14).Bymid-century,changesinaggregatethewetandhotprojectionsshowincreasesinwateryield2020ResourcesPlanningActAssessment9-13Figure9-14.Precipitation,wateryield,andpotentialevapotranspirationforthebaselineperiod(1986to2015).Precipitation(P)WaterYield(Q)PET<50mm>1,000<50mm>1,000<1,000mm>2,000Figure9-15.Spatialchangesin30-yearaverageofannualprecipitationinFigure9-16.Spatialchangesin30-yearaverageofannualwateryieldinresponsetofutureclimatechange,fromcurrent(1986to2015)tomid-centuryresponsetofutureclimatechange,fromcurrent(1986to2015)tomid-century(2041to2070)for:(a)RCP4.5and(b)RCP8.5.(2041to2070)for:(a)RCP4.5and(b)RCP8.5.(a)RCP4.5(b)RCP8.5(a)RCP4.5(b)RCP8.5WetWetWarmWarmMidMidHotHotDryDry<-400>40<-1000>1009-14FutureofAmerica’sForestsandRangelandsforthesesamesubregions.ThemostconsistentresultsVulnerabilitytoWaterShortageacrossprojectionsareincreasesinprecipitationandyieldandSocioeconomicDroughtformuchoftheWesternUnitedStatesanddecreasesinwateryieldintheSouthwest(figures9-14and9-15).Much❖Extendeddryspellsturnshort-termwaterwarmertemperaturesintheSouthareprojectedtoincreasepotentialevapotranspirationmorethanforanyotherregion,shortagesintointenselong-termshortages.amplifyingtheeffectsofdecreasedprecipitationandleadingtofurtherdeclinesinwateryield(figure9-16).Themajority❖Underhighfuturewarming,droughtslastingofriverbasinsintheWesternUnitedStatesareprojectedtoexperienceadecreaseinpotentialevapotranspirationundermorethanayearareprojectedtooccurfourthewetandleastwarmclimateprojectionsbutincreasesintimesmoreoftenandincreaseinintensityby76potentialevapotranspirationunderthehot,dry,andmiddlepercent.projections.LargeincreasesinpotentialevapotranspirationoccurinthesouthernpartsoftheGreatPlainsandNorth❖Medium-intensitydroughtswilloccursixtimesCentralSubregions.moreoftenandseveredroughtswillbe76percentmoresevereby2070underRCP8.5,relativetocurrentconditions.Figure9-17.Spatialchangesin30-yearaverageofannualpotentialWatershortageoccurswhendemandsarepartiallyorevapotranspiration(PET)inresponsetofutureclimatechange,fromcurrentfullyunmet,aconditionalsoreferredtoassocioeconomic(1986to2015)tomid-century(2041to2070)for:(a)RCP4.5anddrought,orjustdrought,forthepurposesofthischapter.(b)RCP8.5.Droughtsaretypicallycharacterizedbytheirmagnitude,duration,frequency,andintensity.Magnitudeisthe(a)RCP4.5(b)RCP8.5cumulativedeficitoverthedurationofthedrought;durationisthenumberofconsecutiveperiodsindrought;frequencyWetistheexpectedarrivaltime(i.e.,returnperiod)ofthedrought;andintensityiscomputedbyitsmagnitudedividedWarmbyitsduration(essentiallytheaveragemagnitudeofthedrought).ThedroughtreturnperiodrepresentshowlikelyaMiddroughtofthatmagnitudeisinanygivenyear.Forexample,a10-yeardroughtwouldbeexpectedtooccuraboutonceHotevery10years,orthatthereisa10-percentchanceofsuchadroughthappeninginanygivenyear.Similarly,a100-yearDrydroughtwouldbeexpectedtooccuraboutonceevery100years,orthatthereisa1-percentchanceofsuchadrought<-100>10happeninginanygivenyear.Intermsofcategorizations,10-yeardroughtsareconsideredmediumintensity,whereas100-yeardroughtsareconsideredsevere.Similardescriptionsarecommonlyusedforfloods(thatis,100-yearfloodsor50-yearfloods)tocreatefloodzonemaps.MethodsformodelingwatersupplyandshortagefollowBrownetal.(2013).Theyrelyonprojectionsofconsumptivewateruse(Brownetal.2019),wateryield(Heidarietal.2020b),streamnetworks,reservoirstoragecapacitywithineachriverbasin,instreamflowrequirements,andtrans-basinwatersystemsandtransfers.Watersupplyinthissectiondiffersfromwateryieldintheabovesectioninthatwatersupplyincludestrans-basindiversions.Instreamflowrequirementsarealsoincludedhereasademandrequirement.WaterisroutedthroughstreamnetworksanddiversionsusingaWaterEvaluationandPlanning(WEAP)modelfortheconterminousUnitedStates(Sieberetal.2002).TheWEAPmodelisrunatthemonthlytimescale,andshortageoccurswhendemand(thesumofconsumptiveuseandinstreamflowrequirements)exceedswatersupply.2020ResourcesPlanningActAssessment9-15DistributionsofshortagesfromtheWEAPresultsareusedfrequencyofbothwithin-year(durationlessthan12months)tocalculatestatisticallikelihoodsofshortageandexpectedandover-year(durationgreatthan12months)shortagesdurationsandfrequencyofdroughtfollowingHeidarietal.occurinthesouthernportionoftheGreatPlains.Inmany(2020a,2021).ThisanalysisimprovespreviousRPAwaterplaces,extendeddryspellsturnshort-termshortagesintoassessmentsbyusingamonthlyratherthanannualtimelong-termintenseshortages,includingthemiddleGreatstepthatallowsanalysisofdroughtswithdurationlessthanPlains,Southwest,andSouth.Thispatternextendsintoayear(sometimescalledflashdroughts)anddroughtsthesouthernRockyMountainswithlowerintensity,aswithdurationmorethanayearbutnotnecessarilyinwellastheNorthCentralSubregion,whichcurrentlyannualincrements.onlyexperienceslow-intensityshortages.ConditionsareprojectedtoimproveslightlyfornorthernFloridaunderRCPFigure9-18showscurrent(1986to2015)shortage4.5butdeterioratesignificantlyunderRCP8.5,especiallyfrequencies,durations,andintensitiesforHUC4basinsforextendedshortages.Althoughclimateprojectionsacrossthecountry.MuchoftheUnitedStatescurrentlywereselectedtorepresentconditionsacrosstheentireexperiencesatleastmoderateshortages.ThesouthernGreatconterminousUnitedStates,precipitationundertheRPAPlainsandRockyMountainSubregions,southernCalifornia,dryclimateprojectionisexpectedtoincreaseinmuchoftheandnorthernFloridaalreadyexperiencehigh-intensitywestcoast,resultinginlessfrequentshortages.shortagesoflessthanamonthinlengthaswellasrelativelylessintenseshortageswithdurationequalorgreaterthan6Inmanyplaces,infrequentextremedroughtsareprojectedconsecutivemonths.tobecomemorefrequent,andthedurationofdroughtsisprojectedtobecomelonger.DroughtsthatcurrentlylastFutureshortagesforthelowerandhigh-atmospheric1monthturninto6-monthdroughts,anddroughtsthatwarmingfutures(RCPs4.5and8.5,respectively)usingthecurrentlylast6monthsturninto12-monthdroughts.Thedryclimateprojectionareshowninfigures9-19and9-20;intensityofdroughtsthatareprojectedtooccurinthefuturetheseprojectionsrepresentaworst-casescenarioformanyperiodevery10,50,and100yearsalsoincreases.WhatregionsoftheconterminousUnitedStates.Underthedrywouldcurrentlybeconsidereda10-yeardroughtisexpectedclimateprojection,conditionsworsenformuchofthecentraltooccur2.5timesmoreoftenunderRCP4.5and6timesUnitedStates.ThemostconsistentincreasesinintensityandmoreoftenunderRCP8.5,withincreasesinintensityandFigure9-18.Intensitiesofwatershortageeventsunderthecurrentconditions(1986to2015)inmillioncubicmeterspermonth.Shortagedurationincreasesmovingfromtoptobottom(durationgreaterthan1month,greaterthan6months,greaterthan12months).Shortagereturn-periodincreasesmovinglefttoright(10-yeardrought,50-yeardrought,100-yeardrought).10year50year100year1mo.6mo.10050012mo.1,0005,000MCM=millioncubicmeters.20,000<50,0009-16FutureofAmerica’sForestsandRangelandsFigure9-19.Changesintheintensitiesofwatershortageeventsfromcurrent(1986to2015)tofuture(2041to2070)conditionsunderRCP4.5.Shortagedurationincreasesmovingfromtoptobottom(durationgreaterthan1month,greaterthan6months,greaterthan12months).Shortagereturn-periodincreasesmovinglefttoright(10-yeardrought,50-yeardrought,100-yeardrought).Locationsmappedinbrownareprojectedtoexperienceincreasingwatershortageintensities,whilelocationsmappedinblueareprojectedtoexperiencedecreasingshortageintensitiesrelativetocurrentshortageconditions.10year50year100year1mo.<-806mo.-5012mo.-20-10-501005001,0005,00020,000<50,000MCM=millioncubicmeters;RCP=RepresentativeConcentrationPathway.Figure9-20.Changesintheintensitiesofshortageeventsfromcurrent(1986to2015)tofuture(2041to2070)conditionsunderRCP8.5.Shortagedurationincreasesmovingfromtoptobottom(durationgreaterthan1month,greaterthan6months,greaterthan12months).Shortagereturn-periodincreasesmovinglefttoright(10-yeardrought,50-yeardrought,100-yeardrought).Locationsmappedinbrownareprojectedtoexperienceincreasingwatershortageintensities,whilelocationsmappedinblueareprojectedtoexperiencedecreasingshortageintensitiesrelativetocurrentshortageconditions.10year50year100year1mo.<-806mo.-5012mo.-20-10-501005001,0005,00020,000<50,000MCM=millioncubicmeters;RCP=RepresentativeConcentrationPathway.2020ResourcesPlanningActAssessment9-17frequencyoccurringintheGreatPlains,Intermountain,detailsoncurrentandfutureconditionsofaquaticspeciesNorthCentral,SouthCentral,andSoutheastSubregions.arediscussedintheBiodiversityChapter.TheresultsfromDroughtsdecreaseinfrequencyinpartsofthePacificthatchapterhighlightthebroadsuiteofriskstoaquaticSouthwestduetotherelativewetnessofthedryclimatesystems,fromclimatechange,lowflows,anddevelopmentprojectioninsouthernCalifornia.Hundred-yeardroughtspressures,andpointtotheroleFederallandsmayplayin(thosewith1-percentlikelihoodinanygivenyear)thatlastpreservingcriticalecosystemservicesandprovidingrefugialongerthanayearareprojectedtoincreaseinintensityby27tothreatenedspecies.percentunderRCP4.5andby76percentunderRCP8.5.Notallnewsrelatedtowaterresourcesisbad.InmanyManagementImplicationsplaces,conservationeffortshavereducedtotalwaterdemand,eveninareaswithsignificantpopulationincrease.InAugust2021,theU.S.DepartmentoftheInteriordeclaredInnovativeprogramsbylocalwatermanagershaveledthefirst-everColoradoRiverBasinwatershortage,triggeringtolargereductionsinhouseholdwateruse.Nevada,foraseriesofwaterusereductionsaccordingtoadroughtexample,recentlypassedalawrestrictingirrigationoflawns,contingencyplanthatwasapprovedbyCongressin2019.or“nonfunctionalturf”(AssemblyBill356).LosAngeles’Underthecontingencyplan,Arizonawilllose18percentMetropolitanWaterDistrictoffers$1persquarefootoflawnofitsannualallocationofColoradoRiverbasinwaterinturfremovedfromresidentialproperties.Similarpoliciesthe2022wateryear,representing8percentoftheState’sthateitherimposerestrictionsorprovideincentivestoreducetotalwateruse;Nevadawilllose7percentofitsColoradoturfgrassarelikelytobecomemorecommon.Riverbasinwater.ThesecutsfallheavilyonagricultureinaffectedStates,wherefarmersandranchersrelyonirrigationConclusionstosupporttheirlivelihoods.Inmanycases,farmershaverespondedtowatershortagesanddroughtbyincreasingMuchofthecountryhasmadeandwillcontinuetomaketheiruseofgroundwater,oftenatratesthatexceedaquiferimprovementsinwateruseefficiency,leadingtodeclinesinrechargerates(HornbeckandKeskin2014,Medellín-totalwithdrawals.However,waterusecontinuestoincreaseAzuara2016).Accordingtomanyoftheprojectionsinthisinareaswithrapidpopulationgrowthandexpandingassessment,suchimpactsonincomes,lifestyles,andotheragriculture.Manyoftheseregionsarealreadyfacingregularnaturalresourceswillbecomemorecommon.watershortages.Whethershortagesincreaseinthefuturedependsheavilyontheclimateoutcome.ProjectedchangesOneofthekeyinsightsformanagementisthataverageinnationalconsumptivewateruserangefroma9-percentfuturewateryieldsarehighlyuncertain,butmorefrequentdecreasetoa235-percentincrease,withthelargestimpactsandintensedroughtsarelikely.Basedontheseinsights,resultingfromtheneedsofagricultureinresponsetowerecommendthatmanagersprepareforamorevariablechangesinprecipitationandaridity.Theseresultshighlightfuture,developingdroughtmanagementplansandpromotingaconundrumassociatedwithclimatechangeandwaterconservationpracticesamongwaterusers.Ourprojectionsuse—adrierclimateleadstoincreasesinwaterdemand.assumewaterusecontinuesaccordingtopasttrends,andBymid-century,changesinaggregatewateryieldacrossthushighlightwhereadaptationmaybeneededasopposedtheconterminousUnitedStatesrangefroma25.7-percenttoidentifyingwhereshortagesmayoccurinthefuture.increaseunderthewetclimateprojectiontoa10.9-percentInregionswherewaterbecomesmorescarce,economicdecreaseunderthedryclimateprojection.pressurewilllikelyshiftwaterusebetweensectorsandregions(Blancetal.2014).LongertermresponsestoclimateWatershortagesareconsistentlyprojectedtoincreaseinchangemightrequiresubstantialtransfersfromagricultureintensity,frequency,anddurationintheSouthwestandGreattourbanusers,whichcouldhaveseriousnegativeimpactsPlainsSubregions.Ifwateryielddecreasesasprojecteddueonruralcommunities(Brownetal.2019,WarziniacktoclimatechangeandshortagesbecomelongerandmoreandBrown2019).Increasingreservoirstoragemightfrequent,theseresultssuggestamixofsupplyanddemandprovideshort-termreliefbutultimatelyreliesonsufficientadaptationmeasuresmaybeneeded.Commonsolutionswateryieldtofillthereservoirs,anincreasingproblemlikegroundwaterminingandtransfersofwaterfromthethroughoutthecountry(Brownetal.2019).Reservoiragriculturaltothedomesticsectorwillworkinsomebutnotlevelsmaybecomelowenoughtoaffecthydroelectricallcases(Brownetal.2019,WarziniackandBrown2019).powerproductions(Craigetal.2018,Boehlertetal.2016,Noveladaptationmethodsmayeventuallybeneeded,suchHendersonetal.2015).asincreaseduseofrecycledwater,expandeduseofprecisionagriculture,moreefficientwaterpricingandtransfers,andLowflowsinriversystemsduetoclimatechangeandhumanupdatedwaterinfrastructure(Gleick2016).usesarealreadyaffectingaquaticbiotaandecosystems,withcompoundingeffectsonwaterqualityandtemperature.MoreProjectionsofwaterusegivenhereassumecontinuationofrecenttrendsineconomicproductionandwateruse9-18FutureofAmerica’sForestsandRangelandsefficiency.TheyarenotboundbyhowmuchwaterisDiehl,T.H.;Harris,M.A.2014.WithdrawalandconsumptionofwaterbyactuallyavailablenordotheyconsiderchangesinwaterthermoelectricpowerplantsintheUnitedStates,2010.U.S.Geologicalscarcityandcompetitionbetweensectors.EstimatesofSurveyScientificInvestigationsReport2014–5184.Reston,VA:U.S.withdrawalsandconsumptiveusearethereforelikelytobeDepartmentoftheInterior,U.S.GeologicalSurvey.largerthanthoseproducedwithmodelsthatmaximizethevalueofwatersubjecttototalwateravailability(e.g.,DraperDiehl,T.H.;Harris,M.A.2019.Withdrawalandconsumptionofwaterbyetal.2003,Pulido-Velazquezetal.2008)andmodelsthatthermoelectricpowerplantsintheUnitedStates,2015.U.S.GeologicalestimatewaterrequirementsneededtomaintaincurrentSurveyScientificInvestigationsReport2019–5103.Reston,VA:U.S.practicesinafuturewithclimatechange(e.g.,MarstonetDepartmentoftheInterior,U.S.GeologicalSurvey.15p.https://doi.al.2020,Strzepeketal.2012).Optimizationmodelstendorg/10.3133/sir20195103.toreflectthebest-casescenarioandmisssomeoftheforcesalreadyoccurringintheeconomythatarelikelytoeitherDieter,C.A.;Maupin,M.A.;Caldwell,R.R.;Harris,M.A.;Ivahnenko,magnifyoralleviatesomeofthepainsassociatedwithT.I.;Lovelace,J.K.;Barber,N.L.;Linsey,K.2018).Estimateduseofclimatechange.OurapproachhighlightswherethestatuswaterintheUnitedStatesin2015.U.S.GeologicalSurveyCircularquoisunsustainableand,therefore,wheremanagement1441.Reston,VA:U.S.DepartmentoftheInterior,U.S.Geologicalactionsaremostneeded.Survey,WaterAvailabilityandUseScienceProgram.65p.Uncertaintyexistsaroundtheseprojections,highlightedbyDraper,A.J.;Jenkins,M.W.;Kirby,K.W.;Lund,J.R.;Howitt,R.E.2003.thevariedresultsforwateryieldacrossclimateprojections,Economic-engineeringoptimizationforCaliforniawatermanagement.butalsoduetounderlyingassumptionsaboutsocioeconomicJournalofWaterResourcesPlanningandManagement.129(3).https://factorslikepopulationgrowthandtechnologicaladaptation.doi.org/10.1061/(asce)0733-9496(2003)129:3(155).Becausedemandcannotexceedsupply,adjustmentsandmitigationmeasuresmaybeneeded.TheRPAAssessmentGleick,P.H.;Cooley,H.;Cohen,M.;Morikawa,M.;Morrison,J.;attemptstocapturethefullrangeofplausiblefuturePalaniappan,M.2009.TheWorld’sWater2008–2009:thebiennialreportconditionstohighlightwheremodelsagreeandwherelargeonfreshwaterresources.Washington,DC:IslandPress.432p.amountsofuncertaintyexist,tohelpmanagersplanfortheworst-casescenario.Heidari,H.;Arabi,M.;Ghanbari,M.;Warziniack,T.2020a.Aprobabilisticapproachforcharacterizationofsub-annualsocioeconomicLiteratureCiteddroughtintensity-duration-frequency(IDF)relationshipsinachangingenvironment.Water.12(6):1552.https://doi.org/10.3390/W12061522.Blanc,E.;Strzepek,K.;Schlosser,A.;Jacoby,H.;Gueneau,A.;Fant,C.;Rausch,S.;Reilly,J.2014.ModelingU.S.waterresourcesunderclimateHeidari,H.,Arabi,M.,Warziniack,T.,&Kao,S.C.2020b.Assessingchange.Earth'sFuture.2(4):197–224.shiftsinregionalhydroclimaticconditionsofU.S.riverbasinsinresponsetoclimatechangeoverthe21stcentury.Earth’sFuture.8(10):Boehlert,B.;Strzepek,K.M.;Gebretsadik,Y.;Swanson,R.;McCluskey,e2020ER001657.https://doi.org/10.1029/2020EF001657.A.;Neumann,J.E.;McFarland,J.;Martinich,J.2016.ClimatechangeimpactsandgreenhousegasmitigationeffectsonU.S.hydropowerHeidari,H.;Arabi,M.;Warziniack,T.2021.Vuln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rg/10.1371/journal.pone.0219242.Thornton,P.E.;Running,S.W.;White,M.A.1997.Generatingsurfacesofdailymeteorologicalvariablesoverlargeregionsofcomplexterrain.Woznicki,S.A.;Nejadhashemi,A.P.;Parsinejad,M.2015.ClimateJournalofHydrology.190(3–4):214–251.https://doi.org/10.1016/changeandirrigationdemand:uncertaintyandadaptation.JournalofS0022-1694(96)03128-9.Hydrology:RegionalStudies.3:247–264.https://doi.org/10.1016/j.ejrh.2014.12.003.Authors:HadiHeidari,UniversityofMassachusetts-AmherstShaundraRasmussen,USDAForestService,RockyMountainTravisWarziniack,USDAForestService,RockyMountainResearchStationResearchStationRyanSwartzentruber,UniversityofTennesseeMazdakArabi,ColoradoStateUniversityPamelaFroemke,USDAForestService,RockyMountainResearchStationRohiniGhosh,PacificCorp,Portland,OR9-20FutureofAmerica’sForestsandRangelandsChapter10Biodiversity:WildlifeandAquaticBiotaFlitcroft,RebeccaL.;Bury,GwendolynnW.;Joyce,LindaA.;Kay,ShannonL.;Knowles,MichaelS.;Nelson,MarkD.;Warziniack,Travis.2023.Biodiversity:WildlifeandAquaticBiota.In:U.S.DepartmentofAgriculture,ForestService.2023.FutureofAmerica’sForestandRangelands:ForestService2020ResourcesPlanningActAssessment.Gen.Tech.Rep.WO-102.Washington,DC:10-1–10-34.Chapter10.https://doi.org/10.2737/WO-GTR-102-Chap10.Biologicaldiversity,orbiodiversity,measuresthemarine,freshwater,andterrestrialsettings.Trackingpatternsvarietyoforganismsandlifeformsinaspecificareainbiodiversity,therefore,iskeytoinformingmanagementandisakeyattributeofhealthyecosystems(Elmqvistetregardingplacesofparticularvulnerabilitytocurrentandal.2003).BiodiversitynaturallyvariesacrosstheUnitedemergingthreats.Statesinresponsetogeologichistory,tectonicactivity,andecoregionalcharacteristics,yetareasofthecountrywithInthischapteroftheResourcesPlanningAct(RPA)naturallylowerbiodiversitystillsupportspeciesofregionalAssessment,wefocusonpatternsandthreatstonativeecological,cultural,andcommercialimportanceandwildlifeandaquaticspeciesbiodiversity,measuredasprovideimportantecosystemservices.Significantdeclinesspeciesrichness.Wepresentbiodiversityinformationatinbiodiversityhavebeendocumentedgloballyacrossmultiplespatialandtaxonmicscales,comparingcurrenttaxonimicgroups(Garcia-Morenaetal.2014)andwithinconditionswiththosepresentedinpreviousreportsandtheconterminousUnitedStates(e.g.,inbirds;seeRosenbergaddingnewapproachesforbetteraddressingbiodiversityetal.2019).DecliningbiodiversityisstronglylinkedtotheconservationintheUnitedStates,withminimalanthropogenicactionsthathavemodifiedecosystemsleadingrepresentationofdistributionsandanalysisforAlaskaandtodeclinesinhabitatquality,quantity,andconnectityinHawaii.Wereportgeographicpatternsofbiodiversity,recent❖Trendsfrombreedingbirdsurveysindicatepopulationdeclinesinatleast20percentofallbirdspeciesacrosshabitattypessincethe1950s/60s,andinmorethan50percentofspeciesthatoccupygrasslandsoraregroundnesting.Thesedeclinesarelinkedtolandusemodificationsofhabitatsaswellasintroducedspeciesandlossofhabitatconnectivity.❖ConcentrationsofimperiledtaxawithalistingstatusundertheEndangeredSpeciesActarefoundacrossthecountry,withparticularconcerninPeninsularFloridaandHawaiiforbirds,andintheRPANorthandSouthRegionsforfishes,crayfish,andmussels.❖WatershedsoftheRPANorthandSouthRegionsaremostvulnerabletocompoundedlandusestress.RegardlessofRPAregion,developmentstandsoutasthelargestoveralllandusestressorfornativeecosystems.❖AreasofpotentialhighclimatestresswereconsistentlyfoundinmountainousareasoftheRPANorth,RockyMountain,andPacificCoastRegions,withpocketsofstressidentifiedinaridregionsoftheRockyMountainRegion.❖Federallandswithalowerriskofdevelopmentorlandconversion,suchasthosemanagedbytheU.S.DepartmentofAgricultureForestServiceandU.S.NationalParkService,areprojectedtobeunderhigherclimatestresscomparedwithotherlands,potentiallylimitingtheirfutureabilitytofunctionasclimaterefugiafornativebiota.2020ResourcesPlanningActAssessment10-1historicaltrendsinpopulations(particularlyofbirds),andmaintainsthemostcomprehensivenationaldataavailablepatternsofspeciesatriskofextinctionasdefinedbytheironthetaxonomy,distribution,andconservationstatusoflistingstatusundertheEndangeredSpeciesAct(ESA).Wenativespecies.Individualspecieswerecountedforeachalsoprovideadiscussionofthreatstobiodiversityincluding250-square-mile(647-km2)gridfromtheNatureServeinvasivespecies,pathogens,currentlanduses,andprojectedspeciesdatasetanddisplayedinmapform(figure10-1).Thefutureclimatechange.datasetincludes4,107totalspeciesfromacrossthecountry(inclusiveofAlaskaandHawaii),capturinginsects,birds,PatternsofBiodiversitymammals,crustaceans,reptiles,andamphibians,amongothers.Ofparticularrelevanceforforestmanagementare❖TheMississippiRiverbasinandMadreanSkythesubsetofthesespeciesidentifiedasforest-associated(seethesidebarAvianSpeciesAssociatedwithForestedIslands/U.S.-MexicoborderareascontaintheEnvironments).highestterrestrialandaquaticbiodiversityacrosstheconterminousUnitedStates.ThesecentersAcrosstheconterminousUnitedStates,thehighestofbiodiversityarelinkedtogeologichistoryandbiodiversityofterrestrialfaunaisfoundintheeasternthelocalizedisolationofspecies(resultinginhighportionsoftheMississippiRiverbasin,intheMadreanratesofendemism).SkyIslands,intheborderareasbetweenTexasandMexico(consistentwithfindingsofVanDevenderetal.2013),❖PopulationtrendsinmigratorygamebirdsandinthesouthAtlantic-andGulf-drainingwatershedsofAlabama,Florida,NorthCarolina,andSouthCarolina.(weblessandwaterfowlgroups)sincetheWesternStatescoverageologicallyyounger,less-dissected1950s/60sexhibitinter-annualvariability,withlandscapethantheeasternportionoftheUnitedStates,harvestgenerallytrackingoverallpopulationleadingtoloweroverallbiodiversityinthisarea(Elkinsnumbers.Overtime,populationsandharvestofetal.2019).ducksandgeesetendtobeincreasing,whilewoodcocksandmourningdovesaredeclining.NativeFish,Crayfish,andFreshwaterMusselBiodiversity❖Long-termpopulationtrendsfrombreedingbirdForthefirsttimeinanRPAAssessment,weareabletosurveysreportstatisticallysignificantdeclinespresentspeciesdistributiondatafornativefish,crayfish,andinallgroupsofbreedingbirds,withatleasthalfmussels,allowingustodescriberegionalcharacteristicsofofallspeciesofgrasslandorground-nestingaquaticspeciesdiversity.Asforterrestrialbiodiveristy,wespeciesshowingsignificantpopulationdeclines.acquireddatasetsofnativeaquaticspeciesfromNatureServeBiodiversityisindeclineglobally,withfreshwateraquaticFigure10-1.Biodiversityofnativeterrestrialspecies(excludingplants)biodiversitydecliningatratesthatexceedmarineormappedataresolutionof250mi2fortheconterminousUnitedStates,withterrestrialecosystems(Tickneretal.2020).IntheUnitedRPAregionalboundariesandtheoutlineoftheMississippiRiverbasininStates,concernaboutspeciesandtheirhabitatshasralliedblue.Invasiveorintroducedspeciesarenotincluded.diversepartnerstouniteinthesharedgoalofecosystemprotectionandenhancement.Inthissection,webeginbypresentingspatialpatternsofterrestrialandaquaticbiodiversity,followedbyapresentationofstatusandtrendinformationforavianspecies.WealsopresentpatternsofimperiledspeciesasdefinedbytheirlistingstatusundertheESA.WeacknowledgethatadditionalspeciesmaybeimperiledacrosstheUnitedStatesthatarenotfederallylistedundertheESA.WeprimarilypresentESA-listedspeciestoprovidedirectinformationtolandmanagerswhohavearesponsibilitytoparticipateinthedevelopmentofconservationplans.NativeTerrestrialBiotaSource:NatureServe.Inordertoassessgeographicpatternsofdistribution,andforreferenceinvulnerabilityassessmentsdescribedlaterinthischapter,wemappedterrestrialbiodiversityacrosstheconterminousUnitedStates.WeacquirednativeterrestrialbiodiversitydatasetsfromNatureServe(https://www.natureserve.org),theorganizationthat10-2FutureofAmerica’sForestsandRangelandsAvianSpeciesAssociatedwithForestedEnvironmentsAcloserlookatlong-termdataavailableonforest-Figure10-2.Estimatedlong-termchangeinthenumberofforest-associatedbirdsisavailablethroughtheNorthAmericanassociatedbirdspeciesdetectedfrom1975to2018.ChangeismeasuredBreedingBirdSurvey(BBS).UsingBBSdatasets,weas1975speciesdividedby2018speciesnumberestimate,excludingfoundthatlong-term(1975to2018)trendsinthenumberexoticspecies.Values<1.0indicatespeciesnumbersincreasing(greenofbirdspeciesassociatedwithforestsvariedamongshades);values>1.0indicatespeciesnumbersdecreasing(purpleshades).ecoregionsoftheconterminousUnitedStates(figure10-2).ThegreatestincreasesinnumbersofforestbirdspeciesSource:USGSBreedingBirdSurvey.wereclusteredinecoregionsofthenorthernGreatPlainsandIntermountainWest,withadditionalgainsscatteredamongtheCrossTimbersandArkansasValley,SouthernTexasPlains,CentralCornBeltPlains,SouthwesternAppalachians,andNortheasternHighlands.ThegreatestdeclinesweredistributedamongtheSouthernRockies,SouthwesternTablelands,andChihuahuanDeserts,andscatteredamongdisjunctecoregionsoftheMojaveBasinandRange,WesternGulfCoastalPlain,NorthCentralHardwoodForests,andAtlanticCoastalPineBarrens(seeBreedingBirdssubsectionofAvianFaunasection,figures10-10,10-11,10-12,10-13).(https://www.natureserve.org/biodiversity-science/species-hotspotinaquaticspeciesbiodiversitygenerally,andforecosystems)andmappedthematthe8-digithydrologiccrayfishinparticular,andistheRPAregionwiththehighestunitcodescale(HUC8;https://water.usgs.gov/GIS/huc.biodiversityoffish,crayfish,andmussels(table10-1).html)acrosstheconterminousUnitedStates(figure10-3).OverallbiodiversityofaquaticbiotaislowestintheRPAWesummarizedindividualspeciesinformationperHUCPacificCoastRegion(table10-1).8intocountstocharacterizebioticrichness.AHUC8isBiodiversitycanbehigherinareaswithmoreendemicintendedtocaptureanentiresubbasinfromtheheadwatersspecies.Forthisanalysis,wedefinedendemismbyRPAtothemouth.InalargeriversystemsuchastheColumbiaregion:speciesendemictoaregionoccuronlyinthatregion.River,therearemultiplesubbasinsattheHUC8scale.BecauseRPAregionsdonotfollowwatershedboundaries,TheNatureServeaquaticbiodiversitydatasetcontains905speciesofnativefishes,391speciesofnativecrayfish,Figure10-3.AquaticbiodiversityoftheconterminousUnitedStatesmappedand304speciesofnativemussels.AllsubspeciesandataHUC8watershedscale,withtheMississippiRiverbasinoutlinedinblue.populationsweremergedintospeciesdesignationsformappingandtabularsummaries.NonnativeorintroducedHUC=hydrologicunitcode.aquaticbiotaarenotincludedinthisassessment.ForSource:NatureServe.example,introducedwarmwaterfishsuchaslargemouthbass(Micropterussalmoides)intheWesternUnitedStatesarenotincludedinthetotalcountofnativefishspeciesinwesternareas.Nativeaquaticspeciesbiodiversityandthedistributionofindividualspeciesvaryinresponsetoadiversityoffactorsincludinggeologicage,patternsofriverconnectivity,latitudeandlongitude,precipitationandthermalregimes,riparianhabitatcomposition(seethesidebarRiparianAreasformoreinformationregardingclassificationofriparianecotonehabitatformanagementapplications),andhumanmodifiersofthelandscapesuchaslanduseandwatermanagement.TheRPASouthRegionisaglobal2020ResourcesPlanningActAssessment10-3Table10-1.NativeaquaticbiodiversityandspeciesendemictoeachRPAAnaccurateunderstandingofthedistributionofspeciesregionforfish,crayfish,andmussels.Numbersarespeciesrichnesscounts,isimportantforbothcurrentandfuturemanagement.withthenumberofendemicspeciesinparentheses.Thismeanshavingaccuratemapsnotonlyforindividualspecies,butalsoforabundanceanddiversityacrosstheRPAregionCombinedFishCrayfishMusselsUnitedStates.TrackingpatternsofoverallandendemicbiodiversityspeciesbiodiversitycanprovideimportantinformationNorth115(4)aboutecosystemhealthbroadly(Bonnetal.2002),inSouthTotalbiodiversity(totalendemic)291(177)additiontothepotentialresilienceoflocalecosystemsRocky(Burlakovaetal.2011).DetectionofchangesandpatternsMountain560(63)354(35)91(24)65(0)inbiodiversityatanationalscaleassociatedwithchangesinPacificCoasttheintensityanddistributionofhumanusesmaybefound1,353(855)702(385)360(293)throughexaminationoftheentiresuiteofspeciespresent(e.g.,BrownandLaband2006),aswellasbyexploring342(59)259(57)18(2)theresponseofendemicspeciestohuman-mediatedchangessuchasclimate,landmanagement,andhuman127(67)109(63)10(2)8(2)populationgrowth.EndemicspecieshavebeenidentifiedaspotentiallymorevulnerabletoclimatechangethanmoreweassignedHUC8watershedslocatedalongborderareaswidelydistributedspecies(Malcolmetal.2006)becausetotheRPAregionthatcontainedthemajorityoftheHUC.manyendemicspeciesoccurwithinasmallandsometimesAllregionshadhighnumbersofendemicspecies(tableisolatedgeographicextent,leadingtonarrowerhabitatand10-1).Thehighestpercentageofbiodiversityidentifiedenvironmentaltolerances.asregionallyendemicwasfoundintheSouthRegion(63percent),followedbythePacificCoastRegion(53percent)(calculatedfromtable10-1).RiparianAreasRiparianecotonesareanimportantnaturalresource,richinSincetheearlysettlementoftheUnitedStates,riparianareasbiodiversity,ecological,andhydrologicalfunctions,supportinghaveexperiencedalterationsresultingfromurbanization,bothaquaticandterrestrialbiodiversity.Further,theseagriculturalactivities,andfloodplaindevelopmentthatalteredecotonescontainspecificvegetationandsoilcharacteristicstheirextentandlandcovercondition(Brinsonetal.1981,thatplayimportantrolesinprotectingwaterqualityandstreamDoppeltetal.1993,Tockneretal.2002).ecosystemhealthandareveryresponsivetolandmanagementactivities(MitschandGosselink1993,Naimanetal.1993).TheNationalRiparianAreasInventoryProjectprovidesfreetoolsandripariandatasetstofacilitateriparianareaFigure10-4.PercentriparianecotoneareaperHUC10watershedindelineationandquantificationonmultiplescales.ThesedatatheNationalRiparianAreasBaseMapin2020.supportmonitoring,riparianlandcoverclassification,riparianconservationprioritization,andriparianareasmanagement.ThenewNationalRiparianAreasBaseMapusestheRiparianBufferDelineationModel(Aboodetal.2012,www.riparian.solutions)todisplayriparianacreage,spatialdistribution,andlandcoveratanationalscale,whereriparianareasaredefinedasstreamsidezoneswithinthe50-yearfloodareaofastream.ThisRiparianAreasBaseMapshowsboththeextentofriparianareasandthegeneralriparianlandcovercomposition,highlightingwhereriparianareascontributedisproportionatelytobiodiversityconservationcomparedtotheirabundance(figure10-4).HUC=hydrologicunitcode.SinanAbood,USDAForestService,WashingtonOfficeBiological&PhysicalResources;LindaSpencer,USDAForestService,ForestManagement,RangelandManagement,andVegetationEcology;MichaelWieczorek,U.S.GeologicalSurvey;andAnnMaclean,MichiganTechnologicalUniversity10-4FutureofAmerica’sForestsandRangelandsAvianFaunain2015,withasubsequentdecreasetonearly39millionbirdsBreedingduckestimate(millionbirds)by2019,amountingtoa55-percentnetincreasesince1990.AlthoughtrendsinterrestrialandaquaticbiodiversityovertimeBreedingpopulationtrendsamongthe10mostcommonduckarenotavailableatanationalscale,species-specifictemporalspecieshavebeenvariable.Relativetopopulationobjectivestrendsforsomeavianfaunaareavailableandprovideinsightsestablishedinthe2018NorthAmericanWaterfowlManagementintotheirpatternsofpopulationabundance.GivenincreasingPlan,8ofthe10mostcommonduckspecies(speciesgroupedthreatstofishandwildlife,examiningpatternsacrossbothforlesserandgreaterscaup,AythyamarilaandA.affinis,timeandspacehelpsusunderstandthepotentialconsequencesrespectively)have2019breedingpopulationsthatexceededofmanagementdecisionsandlocaterisksaswellaspotentialpopulationobjectives,butpintail(Anasacuta)andscauprefugia.Wepresentstatusandtrendsinselectedbirdspecies(greaterandlessercombined)fellbelowobjectivesby43and29usingdatacollectedbytheU.S.FishandWildlifeServicepercent,respectively(figure10-5).Gadwall(Marecastrepera)(FWS)andU.S.GeologicalSurvey(USGS),incollaborationandgreen-wingedteal(Anascarolinensis)bothexceededwithStates,Tribes,privatelandowners,nongovernmentalpopulationobjectivesbymorethan50percent.Mallard(Anasorganizations,andotherFederalpartners.Thesegroupshaveplatyrhynchos),themostabundantduck(9.4millionin2019),responsibilityfortheconservationormonitoringofmigratoryexceededitslong-termpopulationobjectiveby22percent.species(e.g.,waterfowlandneotropicalmigratorysongbirds),federallylistedspecies(endangered,threatened,andproposedDuckharvestnumbersacrosstheUnitedStatesincreasedfromforlisting),andspecieswithspecialdesignationslikethe5.1millionin1961to9.7millionin2019(figure10-6).Duringgoldeneagle(Aquilachrysaetos)andbaldeagle(Haliaeetusthatperiod,harvestratesincreasedtoexceed15millionintheleucocephalus).Thissectiondescribespopulationand1970s,decreasedtobelow5millioninthelate1980s,peakedharvesttrendsinmigratorygamebirdsaswellastrendsinabove17millioninthelate1990s,andthendeclinedpopulationsofbreedingbirds.Wepresenttheseresultsusinggraduallytothecurrentrate.Thenationalpatternofharvesttheorganizationalunitsassociatedwiththesurveysandtrendlowsduringthelate1980sisrepeatedineachoffourflywaysassessmentsassociatedwithdatacollectionratherthaninrelationtoRPAregions,topreservethestatisticalaccuracyoftheFigure10-5.Trendintheduckpopulationfrom1955to2019(top);therelationsourceinformation.betweencurrent(2019)duckpopulationestimates(CP)forthe10principalduckspecies(speciesgroupedforgreaterandlesserscaup)withreferencetoMigratoryGameBirdsthepopulationobjectives(PO)specifiedinthe2018NorthAmericanWaterfowlManagementPlan,measuredaspercentofobjective(bottom).Migratorygamebirdsreportedherecollectivelyrefertowaterfowl(ducks,geese,andswans)andtwoadditionalspecies55definedasweblessmigratorygamebirds:themourningdove(Zenaidamacroura)andAmericanwoodcock(Scolopaxminor).50Migratorygamebirdsareeconomicallyimportantthroughrecreationalharvestandcontributetonativeecosystemsand45biodiversity.Thesebirdshavearigorousmanagementhistorytraceabletoaseriesofinternationalagreementstoconserve40themthatweresignedattheturnofthe20thcentury.Thisfocusedmanagementledtothedevelopmentofwhatmany35considertobetheleadingmonitoringsystemforconterminouslydistributedspecies(Nicholsetal.1995).Populationflywaysor30managementunitshavebeenestablishedtoachieveconsistentmonitoringandmanagementofwaterfowl,mourningdoves,and25woodcock.Waterfowlharvestregulationdecisionsareinformedbypopulationmonitoringdata(Nicholsetal.2007),soitisnot20surprisingthatharvesttrendsmirrorbreedingpopulationtrends(Flatheretal.2013).19551960196519701975198019851990199520002005201020152020YearMigratoryWaterfowl—Ducks,Geese,andSwansSpecies2018populationobjectiveTrendsinthepopulationsofmigratorywaterfowl,includingScaupspp.ducks,geese,andswans,varyovertime.BreedingduckCanvasback20406080100120140160180populationestimatesin2019were2percentlowerthanin1955RedheadPercentofpopulationobjective(CP/POx100)and10percenthigherthanthelong-term(1955to2019)average(figure10-5).Afterfallingtorecordlowsin1990(25millionNorthernShovelerbirds),duckpopulationsincreasedtoalmost50millionbirdsBlue-wingedTealGreen-wingedTealAmericanWigeonGadwallPintailMallard0Source:U.S.DepartmentoftheInterior,U.S.FishandWildlifeService.2020ResourcesPlanningActAssessment10-5trackedbytheFWS(i.e.,Pacific,Central,Mississippi,andpopulationsegmentsofvaryingsize.PopulationandharvestAtlantic)(figure10-6).Similarly,gooseharvest—includingestimatesarereportedforEasternversusWesternU.S.Canadageese(Brantacanadensis),brant(Brantabernicla),regions.In2019,thetotalswanpopulationwasestimatedsnowgeese(Chencaerulescens),Ross’sgeese(Chenrossii),at194,000birds,nearlyidenticaltotheestimateof193,000emperorgeese(Ansercanagicus),andwhite-frontedgeesebirdsfrom1985.Fluctuationsinpopulationsrangedfrom(Anseralbifrons)—increasedslowlyfrom0.65millioninalowof158,000in1993toahighof270,000in2007and1961to1.82millionin1991,thenincreasedsubstantiallyto2008.Easternandwesternpopulationsexhibitsimilartotal3.82millionin2008.Sincethen,theharvestratehasbeennumbersandtrends(figure10-7).Swanharvestestimatesmorevariable,withaslightlydecreasingtrendthroughthehavebeenvariable,withincreasingtrendssimilarto2019harvestrateof2.69millionbirds(figure10-6).populationsfrom1962to2019(figure10-7).Swanpopulations(onlytundraswans,Cygnuscolumbianus)Figure10-7.Nationaltrendsforthewesternandeasternregions(top)foraremonitoredbytheFWSthroughsurveysofmanyseparateswanpopulationfrom1980to2019(middle)andswanharvestfrom1962to2019(bottom).Figure10-6.NationaltrendsacrossFWSadministrativewaterfowlflywayboundaries(top)fortotalduckharvest(middle)andtotalgooseharvestSwanmanagementregions(bottom),from1961to2019.WaterfowlFlyways1961–2019waterfowlharvest(millionsofbirds),byflywaySwanpopulation(thousands)SwanharvestYearYearFWS=U.S.FishandWildlifeService.Source:U.S.DepartmentoftheInterior,U.S.FishandWildlifeService.Source:U.S.DepartmentoftheInterior,U.S.FishandWildlifeService.10-6FutureofAmerica’sForestsandRangelandsWeblessMigratoryGameBirds—AmericanFigure10-8.AmericanwoodcockFWSadministrativemanagementregionsWoodcockpopulationindexWoodcockandMourningDove(top);populationindexfrom1968to2019(middle);andharvesttrendsfrom1999to2018(bottom).Americanwoodcockpopulationsandharvesthavedecreasedoverthepast50years.Americanwoodcocksinging-groundWoodcockmanagementregionssurveys(SGS)havebeenconductedalongpermanentsurveyroutesbytheFWSeachspringsince1968(SeamansandRauYear2020),andpopulationsarereportedasanindexofaveragenumbersofbirdsdetectedperSGSroute.WoodcockSGSindiceshavedecreasedconsistentlyinboththeEasternandCentralmanagementregions(figure10-8).Onaverage,4.0woodcockweredetectedperSGSroutein1968,decreasingto2.4birdsin2019(figure10-8).Woodcockharvestrateshavealsodecreased,fromnearly500,000birdsin1999to180,000birdsin2018,withharvestsintheEasternandCentralmanagementregionsdecreasingbysimilarproportions(figure10-8).FortheperiodduringwhichbothSGSandharvestratesarereported(1999to2018),thewoodcockpopulationindexdecreasedfrom3.0to2.3birdsperroute.Mourningdoveshavedeclinedinabundancefrom352milliondovesin2003to183milliondovesin2019,a3.5-percentaverageannualrateofdecline(figure10-9)(contactchapterauthorsforextensivereferencelistofdatasources).Averageannualratesofchangeduringthisperiodwere−3.3percentintheEastern,−0.5percentintheCentral,and−5.1percentintheWesternFWSmanagementunits(figure10-9).Mourningdoveharvestshavealsodeclined,from24millionin1999to10millionin2019(figure10-9).Fortheperiodduringwhichpopulationestimatesarereported(2003to2019),harvestrateschangedataverageannualratesof−3.5percentintheEastern,−2.0percentintheCentral,and−3.5percentintheWesternmanagementunits,foranoveralldeclineof2.8percentperyear.Woodcockharvest(thousands)YearFWS=U.S.FishandWildlifeService.Source:singing-groundsurveys(SGS)conductedbytheU.S.DepartmentoftheInterior,U.S.FishandWildlifeService.2020ResourcesPlanningActAssessment10-7Figure10-9.MourningdoveFWSadministrativemanagementunits(top);managedbytheUSGSthatprovidestrendsintherelativepopulationtrendsfrom2003to2019(middle);andharvesttrendsfrom1999abundanceofmorethan400birdspeciesnationwide(Robbinsto2019(bottom).etal.1986).BBSpopulationtrendsaresummarizednationallyandbyindividualBirdConservationRegions(BCR;figureDovepopulation(millions)10-10),whichdelineateecologicallydistinctregionsinNorthAmericawithsimilarbirdcommunities,habitats,andresourcemanagementissues.ThirtyBCRsarelocatedintheconterminousUnitedStatesandareincludedinthisreport(https://nabci-us.org/resources/bird-conservation-regions/).Toobtainmoredetailedunderstandingofhowbirdsrespondtochangesintheirenvironments,wegroupedbirdspeciesbybreedinghabitattype(grassland,successional-scrub,wetland,woodland),nesttypeandlocation(cavity,ground-low,midstorycanopy,opencup),andmigrationstatus(neotropical,permanent,shortdistance).DetailsondatasourcesandmethodsarereviewedinFlatheretal.(2013).Trendsinabundancearereportedforlong-term(1966to2019)andshort-term(1993to2019)timeperiods.Directionandstatisticalsignificanceofpopulationtrendsarelabeledashavingsignificantincrease,nonsignificantincrease,nonsignificantdecrease,orsignificantdecrease,basedonahierarchicalmodelingapproach(SauerandLink2002)thatprovidesaconvenientframeworkforsummarizingpopulationchangeamongregions.Long-termpopulationtrendsfrombreedingbirdsurveysshowdeclinesinmostcategoriesofbirdsdefinedbyhabitattype.Doveharvest(millions)Figure10-10.BirdconservationregionsoftheUnitedStates.FWS=U.S.FishandWildlifeService.YearSource:PopulationdatafromU.S.DepartmentoftheInterior,U.S.FishandWildlifeService.BreedingBirdsSource:NorthAmericanBirdConservationInitiative(https://nabci-us.org/resources/bird-conservation-regions/).Wildbirdpopulationshavelongbeenconsideredgoodindicatorsofenvironmentalthreatslikelandscapechangebecausechangesinhabitataffecttheabundanceanddiversityofbirdspeciesthatoccupyaparticularregion(FlatherandSauer1996,Pidgeonetal.2007).GiventhatNorthAmericanbirdpopulationshavedeclinedby29percentsince1970,anetlossofnearly3billionbirds(Rosenbergetal.2019),itisimportanttoevaluatethestatusandtrendsamongbirdspeciesthroughoutthecountry.ReportedbreedingbirdtrendsarebasedontheNorthAmericanBreedingBirdSurvey(BBS),anannualsurvey10-8FutureofAmerica’sForestsandRangelandsLong-TermAbundanceTrendsspecieshavestatisticallysignificantincreasingordecreasingpopulations(figure10-12).ThismaybepartiallyexplainedFrom1966to2015,statisticallysignificantdecreasesinbirdbysmallersamplesizesavailableduringshorterperiods.populationsexceededsignificantincreasesforspeciesinTrendsformidstorycanopynestersandneotropicalmigrantsgrasslandandsuccessional-scrubhabitats;speciesthatbuilddifferedfromlongertermtrends;thesegroupshadmoreground-low,midstory,andopen-cupnests;andspecieswithspecieswithstatisticallysignificantincreasingpopulationsinneotropicalorshort-distancemigrationpatterns(figure10-11).theshortterm(figure10-12).Grasslandbirdspecieshadthegreatestdeclinesinlong-termtrends,with54percentofspeciesshowingsignificantTrendComparisonsdecreaseswhileonly4percenthadsignificantincreases.Theremaining42percentofgrasslandbirdsexperiencedAcrossallthehabitataffinitygroupings,allBCRshadatpopulationchangesthatwerenotstatisticallysignificant.Theleastonebirdspeciesthatshowedstatisticallysignificantcavitynestingcategorycontainedthelargestpercentageofpopulationgainsoverboththelongterm(1966to2019)specieswithstatisticallysignificantincreasingpopulations(37andtheshortterm(1993to2019)(see“All”infigure10-percent),butthiswasmostlyoffsetbysignificantlydecreasing13).Whenexaminingindividualhabitataffinitygroups,populations(29percent).Othercategorieswheresignificantlypatternsofincreasingordecreasingpopulationsvaried.increasingpopulationsexceededdecreasingpopulationsGrasslandspeciesarealmostuniversallyindeclineoverincludedwetlandhabitatusersandpermanentresidents.bothlong-andshort-termassessments(figure10-13).Successional-scrub-associatedspeciesintheNorthRegionShort-TermAbundanceTrendsandSoutheastSubregionalsoexperiencedpopulationdeclinesoverbothtimeperiods.SomeincreasesinwetlandPatternsofspeciespopulationsoverthe2005to2015periodspeciesinthenorth-centralportionoftheUnitedStatesmirrorlongertermtrends;however,smallerproportionsofFigure10-11.Long-termincreasesanddecreasesinproportionsofnativeFigure10-12.Short-termincreasesanddecreasesinproportionsofnativebirdpopulationsintheconterminousUnitedStates,1966to2015.Long-birdpopulationsintheconterminousUnitedStates,2005to2015.Short-termproportionofnativebirdspecieswithdecreasingpopulationsshownintermproportionofnativebirdspecieswithdecreasingpopulationsshowninredandincreasingpopulationsshowninblue.Changesthatarestatisticallyredandincreasingpopulationsshowninblue.Changesthatarestatisticallysignificantappearinadarkshade;nonsignificantchangesappearinalightsignificantappearinadarkshade;nonsignificantchangesappearinalightshade.Speciespopulationsareanalyzedbasedonmajorhabitataffinity,shade.Speciespopulationsareanalyzedbasedonmajorhabitataffinity,nestingposition,andmigratorystatus.nestingposition,andmigratorystatus.Source:USGSBreedingBirdSurvey.Source:USGSBreedingBirdSurvey.2020ResourcesPlanningActAssessment10-9arenoted(figure10-13).WetlandspeciesintheTexasImperiledAnimalSpeciesborderlandsregionexperiencedsignificantlydecreasingpopulationsintheshortterm,alongsideincreasing❖ConcentrationsofESA-listedbirdsarepopulationsoverthelongterm(figure10-13).documentedinPeninsularFloridaandHawaii,Figure10-13.DecreasingorincreasingnativebirdpopulationsinthewhereaslistedmammalsandfisharewidelyconterminousUnitedStates,byBirdConservationRegion.Proportionofdistributed,withregionalconcentrationsacrossnativebirdspecieswithdecreasing(red)orincreasing(blue)populationsmultipleareas.estimates,bymajorhabitataffinity,overthelongterm(1966to2019;left)andshortterm(1993to2019;right).Grayareasdenotewheretherewere❖RegionallyconstrainedESA-listeddistributionsinsufficientroutesforobservingspecies.wereidentifiedforamphibians(CoastalSource:USGSBreedingBirdSurveyandNorthAmericanBirdConservationInitiative.California),crustaceans(CoastalMountainsandDrySteppe),mollusks(UpperMidwest,SouthernAppalachia,andInteriorHighlandHillsandPlateau),andreptiles(GulfCoastandPeninsularFlorida).TheprotectionofnativebiotatoavoiddeclineandtheconservationofspeciesalreadyindeclinearebothprimarygoalsofStateandFederalagencies.Thisimportantworkaddresseschangesinhabitatandenvironmentalconditionsresultingfromavarietyofcausesthataffectsomeofourmosticonicandculturallyimportantspecies(seethesidebarPacificTroutintheConterminousUnitedStates).Inthissection,wedescribepatternsinthedistributionoffederallyidentifiedimperiledspecieslistedundertheESAbecausetheirconservationstatusislinkedtoappliedmanagementactionswithintheUnitedStates.WealsopresenthotspotsfortaxonomicgroupsanddescribetaxaidentifiedasSpeciesofGreatestConservationNeedfromacrossthesetoffederallymandatedStateWildlifeActionPlans,whichguidebiodiversitymanagementandconservationactionsattheStatelevel.FederallyListedImperiledSpeciesFederallistingdemonstratesbothempiricalevidenceofspecies-specificlong-termpopulation-scaletrends,aswellaspoliticalwillinsupportoflistingdecisions.WefocusonESA-listedspecies,specificallyspecieslistedasfederallyendangered,threatened,proposedendangeredorthreatened,candidate,speciesofconcern,orlistedthreatenedbecauseofsimilarityinappearancetoanotherspecies(definitionofthesespeciescodescanbefoundat:https://www.fws.gov/endangered/about/listing-status-codes.html).Werefertothisbroadassemblageofspeciesasimperiledthroughoutthischapter.SpeciesassignedG1orG2conservationstatusbyNatureServearenotincludedinthisanalysisbecausetheyarenotfederallylistedundertheESA,butthesespeciesareincludedinthesidebarForest-AssociatedSpeciesatRiskofDecline.DistributionsofESA-listedtaxavarygeographically,withsomeportionsofthecountrycontaininghighernumbersoflistedspeciesthanothers.Hawaiihasthelargestnumberoflistedspecies(499;mostlyfloweringplants),nearlydoublethesecondhighestState,California(286).StateswiththefewestlistedspeciesincludeWashington,DC(3),Vermont(6),NorthDakota(8),andAlaska(8)10-10FutureofAmerica’sForestsandRangelands(https://ecos.fws.gov/ecp/report/species-listings-by-state-SouthernAppalachia,andInteriorHighlandHillsandtotals?statusCategory=Listed).Forthisassessment,speciesPlateau),andreptiles(GulfCoastandPeninsularFlorida)distributionsacrosstheUnitedStatesweremappedontoan(figure10-14).equal-areagrid(250squaremiles[647km2])toeliminateareaeffectsofStateorcountysize(figure10-14).ImperiledThetotalnumberofESA-listedspeciesaretrackedbybirdsarewidelydistributed,withnotablehotspotsinHawaiitheFWS,EnvironmentalConservationOnlineSystemandPeninsularFlorida(figure10-14).Imperiledmammal(https://ecos.fws.gov/ecp/report/boxscore).Weplottedthisandfishspeciesarealsowidelydistributed,butwithinformationfromJuly1976throughOctober2021andsawamultipleregionalareasofconcentration(figure10-14).Moresteadyriseintheoverallnumberoffederallylistedimperiledregionallyconstraineddistributionsareevidentforimperiledspecies,withsharpincreasesinaquatictaxa(e.g.,fish,amphibians(CoastalCalifornia),crustaceans(Coastalmussels)andinsects(figure10-15).WithfewspeciesbeingMountainsandDrySteppe),mollusks(UpperMidwest,delisted,currentpatternsofdistributionreflectcumulativecountsofspeciesthathavebeenfederallylistedovertime.Figure10-14.Geographicdistributionsofplant,mollusk,coral,bird,crustacean,insect,arachnid,mammal,fish,amphibian,andreptilespeciesformallylistedundertheEndangeredSpeciesActasendangered,threatened,proposedendangeredorthreatened,candidate,speciesofconcern,orlistedthreatenedbecauseofsimilarityinappearancetoanotherspecies.AlaskaandHawaiiaredisplayedatadifferentscaleforpresentationpurposes.Source:NatureServe.2020ResourcesPlanningActAssessment10-11Figure10-15.CumulativenumberofspecieslistedasendangeredorForest-AssociatedSpeciesatRiskofDeclinethreatenedundertheEndangeredSpeciesAct(accountingfordelistings)from1July1976through4October2021forplantsandanimals(top),vertebrateForest-associatedspeciesaretrackedbyNatureServegroups(middle),andinvertebrategroups(bottom).Increasesinagivenyearthroughahabitatmatrixdomaintabledevelopedforeachareadditionalspeciesadded,makingthetotalnumberofspeciesinagivenspecies(NatureServeCentralDatabases,metadataonfileyearcumulativeovertime.withMichaelS.Knowles,RockyMountainResearchStation).Weexaminedforest-associatedspeciesthatwereESA=EndangeredSpeciesAct.classifiedbyNatureServewithconservationstatusG1Source:FWSEnvironmentalConservationOnlineSystem(https://ecos.fws.gov/ecp/report/boxscore).(criticallyimperiled),G2(imperiled),orG3(vulnerable).Thislistincludes,butisnotlimitedto,federallylistedESAspecies.Amongforest-associatedspeciesofvascularplants,vertebrates,andselectinvertebrates,111(~1percent)weredeterminedtobepresumedorpossiblyextinct;5,328(31percent)weredeterminedtobeatriskofextinction(includesspeciesclassifiedascriticallyimperiled,imperiled,orvulnerabletoextinction);and12,025(69percent)weredeterminedtobeapparentlysecureorwereunranked.At-riskspeciesassociatedwithforesthabitatsareconcentratedgeographicallyinHawaii,thearidmontanehabitatsoftheSouthwest,thechaparralandsagehabitatsofMediterraneanCalifornia,andinthecoastalandinlandforestsofnorthernandcentralCalifornia.Thenumberofpossiblyextinctandat-riskspeciesisproportionatelygreatestamongvascularplants(32percent)andselectinvertebrates(34percent)—nearlydoublethepercentageobservedamongvertebrates(19percent)(figure10-16,left).Amongforest-associatedvertebrates,thegreatestproportionofpossiblyextinctandat-riskspeciesisfoundamongamphibians(37percent).Birds(16percent),reptiles(14percent),freshwaterfishes(13percent),andmammals(12percent)showsubstantiallylowerpercentagesofforest-associatedspeciesconsideredtobeatrisk(figure10-16,right).Figure10-16.Thepercentofvascularplant,vertebrate,andselectinvertebratespeciesassociatedwithforesthabitatsdeterminedtobepossiblyextinct,atriskofextinction,secure,orunranked(left).Changeinthepercentofforest-associatedamphibian,bird,freshwaterfish,reptile,andmammalspeciesclassifiedasat-riskusingNatureServeglobalconservationstatus(G1,G2,G3)asdescribedintheNationalReportonSustainableForestsfrom2003,2010,2015,and2020(right).Source:NatureServeandmultiplesustainabilityreports.10-12FutureofAmerica’sForestsandRangelandsPacificTroutintheConterminousUnitedStatesPacifictrout(Oncorhynchusspp.)areecologically,resourcesandwildplacesunderachangingclimate.socioeconomically,andculturallyimportant.SubstantialLegaciesofpastoverfishingandland-useactivitieshavedeclinesinabundanceandcontractionsindistributionledtohabitatdegradation(e.g.,fromforestharvest,acrossPacifictroutspeciesandsubspecieshaveledtoagriculture,cattlegrazing,mining,migrationbarriers,substantialresearchandconservationefforts(figurenonnativespecies,climatechange,landdevelopment,10-17).Populationdeclinesofatleasttwo-thirdsfromwaterwithdrawal,etc.).Fortunately,Pacifictrouthavehistoricallevelsforsomepopulationshaveledtoevolvedcharacteristicsincludinggenetic,phenotypic,andelevatedFederalprotection(undertheESA)andbyStatelife-historydiversity,alongwithlong-distancemigrationmanagementagenciesinallorpartoftheirrange.Twotoberesilienttolarge-scalenaturaldisturbances(e.g.,cutthroattroutsubspecies,theAlvordcutthroattrout(O.wildfire,flood).Thesecharacteristicsmaybethekeysclarkiialvordensis)andtheyellowfincutthroattrout(O.totheirfuturepersistence.Scientistsandmanagerscanclarkiimacdonaldi),areconsideredextinct.worktogethertoconsidersocialpressuresthatincreasevulnerabilityofPacifictroutandfindopportunitiestoHumaninfluencesleadingtodeclinesinPacifictroutrestorespeciesdiversitythroughflexiblemanagement.beganwithEuro-AmericancolonizationofNorthAmerica(Penalunaetal.2016).ThedeclineofPacifictroutoverBrookePenaluna,USDAForestService,PacificNorthwestrecentdecadesand,insomecases,thelastcentury,reflectsResearchStationthechallengesofbalancingsocietalvalueswithnaturalFigure10-17.HistoricalandcurrentdistributionsofPacifictroutintheconterminousUnitedStates,withdistributionsofOncorhynchusmykissspp.andotherPacifictrout(left),andO.clarkiispp.(right).Historicaldistributions(fadedcolors),representareasthatarenolongeroccupied.Source:ModifiedfromPenalunaetal.2016.2020ResourcesPlanningActAssessment10-13State-LevelSpeciesofConcernThreatstoBiodiversityInadditiontoFederalagencies,individualStatesandTribal❖Theaggregateindexoflandusestressshowsgovernmentsalsoconductwildlifeandfishmanagementconservation.MaintaininganapprovedStateWildlifethestarkdifferenceinpressureineasternActionPlan(SWAP;https://www.fishwildlife.org/afwa-comparedwithwesternwatersheds.Easterninforms/state-wildlife-action-plans)isaprerequisitetowatershedsfacecompoundedpressuresfromreceivingFWSStateandTribalWildlifeGrantProgrammining,energydevelopment,nitrogendeposition,funding.AllStatescompletedinitialSWAPsin2005andandroads,whereashigh-riskwatershedsintheupdatedSWAPsin2015.EachSWAPidentifiesSpeciesWesternUnitedStatesfacepressuremainlyfromofGreatestConservationNeed(SGCN)withinaState—developmentinlargemetropolitanregions.manyofwhicharenotfederallylisted—aswellastheirkeyhabitatsandthreats,andactionsneededtoconserve❖AlthoughthePacificCoastandRockyMountainthem.ToillustratethediversityofspeciesofimportancetoeachState,wereportthenumbersofSGCNsbyRegionsexhibitlowlevelsofaggregatelandtaxonomicgroup,State,andRPAregion,basedonaUSGSusestress,pocketsofhighstressoccurinthecompilationofSWAPdata.humanpopulationandagriculturalcentersofNotallStatesconsideredalltaxonomicgroups,nordidWashington,Idaho,andCalifornia,andareasoftheyconsiderallspecieswithintaxonomicgroupswhentheRockyMountainsthatareexperiencingrapiddesignatingSGCN.Forexample,fewStatesincludedplantpopulationgrowth.species.Therefore,wepresentinformationforamphibians,fish,mollusks,reptiles,birds,andmammalsformore❖AreasofhighclimatestresswerefoundinallconsistentcomparisonsamongStates.AcompilationofSWAPsacrossall50Statesand5RPAregions.Amajorityofourclimatechangeterritoriesrevealed4,723SGCNin2005and4,484SGCNmodelsprojectfuturehighclimatestressinthein2015,resultingin5,525distinctSGCN.The2015SWAPmountainsofthePacificCoast,RockyMountain,taxonomicbreakdownincluded289amphibians,865birds,andSouthRegions,aswellasinlargeareasfrom1,180fish,518mammals,1,253mollusks,and379reptiles.NewYorktoMaineintheNorthRegion.LowerTheRPASouthRegionhadnearlytwiceasmanySGCNelevationlandsinsouthernNewMexico,southerncomparedtoeachoftheotherthreemajorRPAregionsArizona,Oklahoma,andTexasarealsoprojected(figure10-18).TheSouthRegionalsohadthemostSGCNtoexperiencehighclimatestress.foramphibians,fish,mollusks,andreptiles;birdandmammalSGCNsweremostnumerousinthePacificCoast❖USDAForestServiceandU.S.NationalParkRegion(figure10-18).ServicelandsareprojectedtoexperiencehigherFigure10-18.CountofspeciesofgreatestconservationneedlistedinStatefutureclimatestressthanallotherlands,likelywildlifeactionplansbyRPAregion,2015.duetotheirlocationinvulnerablehigherelevationareas.TheseresultssuggestthattheabilityofDatacollectedbyU.S.FishandWildlifeServiceandcompiledbyU.S.GeologicalSurvey.theselandstoserveasclimaterefugiafornativebiotaandecosystemsmaybelimited.❖OverlaysofclimatestressandterrestrialoraquaticbiodiversityindicatethatplacesofhighclimatestressandhighbiodiversityarecommonlyfoundintheNorthandSouthRPARegions,althoughpocketsofhighstressandhigherbiodiversityarealsofoundinthePacificCoastRegion.Nativespecieshaveexperiencedsignificantlossesinhabitatowingtoawidevarietyofthreatsderivedfromhuman-drivenlanduseandmanagement(Foleyetal.2005)thatwilllikelybecompoundedinthefutureasthestressonnativeecosystemsincreasesunderachangingclimate(Manytka-Pringleetal.2015).Inthissection,wedescribeongoingstressorsaffectingnativeecosystems,includinginvasivespecies,pathogens,andlandusealteration—withafocusonurbanareas,agriculture,mining,pipelines,andenergydevelopment.Wealsoincludeasectionexaminingecosystemstressrelatedtoclimateprojectionsunderfuturescenarios.Finally,weoverlayexistinglandusestresswithmodeledclimatestressandconsiderclimatestressrelative10-14FutureofAmerica’sForestsandRangelandstodistributionsofnativeterrestrialandaquaticbiota.TheseInvasiveSpeciescomparisonshighlightthedifferentstressorscurrentlyaffectingspecificregions,andplacesoffutureconcern,InvasivespeciesintheUnitedStatesarehighlydiverseandparticularlyconsideringbiodiversitydistributions.representeverytaxon.Morethan6,500invasivespecieshavebeendocumentedascurrentlyestablished(seeUSGS,BiologicalDriversofChangehttps://www.usgs.gov/programs/invasive-species-program;OTA1993),andeachspecies’levelofimpactisasvariedasInvasivespeciesandpathogensaresignificantdriversoftheorganism.Invasivespeciesaredefinedhereasplentiful,changeinbiodiversityacrosstheUnitedStatesandarenonnativeorganismsthatnegativelyaffecttheareatheyanticipatedtoincreaseininfluenceasindividualspeciesinhabit(Becketal.2008,ColauttiandMacIsaac2004).respondtoanthropogenicdriversoflanduseandclimateInvasiveindividualsandspeciescompeteforresourcesandchange.Neitherofthesetopicshavebeenaddressedinpredatenativespecies(Dohertyetal.2016,Doodyetal.priorRPAreports.Inthisreport,weintroducethesetwo2009,Duggeretal.2011,Saloetal.2007),andmayalsodriversofecologicalchange,anddescribesomeoftheinterbreedandhybridizewithrelatednativeorganismsmechanismsthroughwhichtheyalterecosystems.Wedid(Huxel1999,Muhlfeldetal.2017).Invasivespeciesnotmodeleitherinvasivespeciesspreadorpathogensbutcontributetohabitatchangeanddestruction,whichcanacknowledgethatsucheffortswouldbehighlyinformativeleadtochangesintrophicstructureordisturbanceregimesforlocal,regional,ornationalmanagementplanningand(Johnsonetal.2009,Sousaetal.2009,MackandD’Antonioimplementation.1998,Vitousek1990).Inthemostseverecases,introducedHerpetofaunaDiversityandThreatsAquatic-dependentherpetofaunaenrichfreshwater,percentofworldamphibians(IUCN2020a)andoverriparian,andmoisture-richecosystems.Therearemorehalfofworldturtlesandtortoises(Stanfordetal.2020)than300amphibianspeciesintheUnitedStates,with70threatenedwithextinction.AlthoughU.S.herpetofaunapercentbeingendemic.Notably,theUnitedStatesisthearefaringbetter,about27percentoffreshwaterturtles,globalhotspotforsalamanderbiodiversity(198species),21percentofsalamanders,and13percentoffrogsandwithAppalachianandPacificNorthwestforestshavingtoadsarethreatened(IUCN2020b).Althoughhabitatparticularlyuniquecommunities.Amongtheworld’slossispervasive,diseasesandclimatechangearelargestsalamandersaretheawe-inspiringhellbendersemergingthreatsthataregainingconservationconcernfor(Cryptobranchusalleganiensis)(to~29inches)andmanagementaction(Bletzetal.2022,OlsonandPilliodcommonmudpuppy(Necturusmaculosus)(to~17inches)2022,Woganetal.2022).Snakefungaldisease,snakeofEasternU.S.waters,andthenorthweststream-breedinglungparasites,turtleshelldisease(fungalpathogen),turtlePacificgiantsalamanders(Dicamptodonspp.),thelargestauralabscesses,turtleandamphibianranavirusinfections,terrestrial-occurringsalamander(to~12inches).Oftheamphibianchytridiomycosis,andtrematodeinfectionsmorethan300U.S.reptiles,freshwater-dependentspeciesareamongleadingconcerns(NWDC2021,PARC2021).includeturtles,snakes,andalligators.TheUnitedStatesForestallinghuman-mediateddiseasetransmissionisatopissecondintheworldinfreshwaterturtlebiodiversity,biosecuritypriority,especiallyforaquaticpathogensthatwithmostofits57speciesoccurringintheSoutheast.arealsoinvasivespeciessuchasthechytridfungi(JulianBothamphibiansandreptilesarecentrallypositionedasetal.2020;NWCG2017,2020;Olson2022).Foraquaticbothpredatorsandpreyinfoodwebs,beingcriticalcogsherpetofaunaintheUnitedStates,climatechangeisofcomplextrophicsystems,cyclingenergyandnutrientsprojectedtoalteramphibian,reptile,andpathogenhabitatbetweenwaterandland.Someamphibiansplayaroleinmacro-andmicro-refugia,generallymovingoptimalcarbonsequestrationfromtheatmosphere(BestandWelshconditionsnorthwardandhigherinelevation,raising2014,Semlitschetal.2014),andbothamphibiansandconcernsforrarespeciesalreadythreatenedbyhabitatlossreptileshavebeenpivotalforbiomedicalresearch.Theirandfragmentation,andrequiringproactiveretentionofecosystemservicesspanavarietyofaesthetic,cultural,predictedhabitatstrongholdsandcorridorsfordispersaleducational,recreational,food,medicine,andother(Olson2022).productcategories.DeannaH.Olson,USDAForestService,PacificNorthwestHerpetofaunaepitomizetheongoingsixthmass-extinctionResearchStationeventonEarth(WakeandVredenburg2008),with402020ResourcesPlanningActAssessment10-15speciescanleadtolocalextirpationorextinctionofnative2009,Garwoodetal.2020).Ontheotherendofthespectrum,species(ClaveroandGarcia-Berthou2005,Huxel1999):somepathogenshaveledtoentirespeciesbecomingendangeredImpactsofinvasivespecieswereimportantin68percentoftheorevenextinct(Pedersenetal.2007,Skerrattetal.2007,SmithextinctionsofNorthAmericanfreshwaterfishesinthepast100etal.2006).Forexample,WhiteNoseSyndrome,causedyears(Milleretal.1989).bythefungalpathogenPseudogymnoascusdestructans,hasdecimatedpopulationsofbatsintheconterminousUnitedStatesThedamageinvasivespeciesinflictoneconomicandecosystem(Chengetal.2021,Hoytetal.2021).Severediseaseoutbreaksserviceshumansuseisalsoextensive(Bornetal.2005,CharlesmayinfluencetheworkingsofentireecosystemsorinfluenceandDukes2008,Polandetal.2021).Themonetarycostofdisturbanceregimes(HilkerandSchmitz2008,Tompkinsinvasivespeciesmanagementisestimatedatapproximately$120etal.2011).billioneachyear(Pimenteletal.2005),withthecropdamagefromEuropeanstarlingsaloneestimatedat$800millionintheTheseverityofdiseaseispredictedtoincreaseinthefutureyear2000(Linzetal.2007).Understandingofinvasivespeciesasintroducedspeciesbringnovelpathogensintonativeisbothincompleteandimportantformanagementofnaturalpopulations,climatechangeinfluencesspeciesrangessystemsoftheUnitedStates(Raheletal.2008).Invasivespecies(includingthoseofpathogens),andhumanalterationstoareanticipatedtoincreaseinthefuture,aswilltheircompoundedlandscapesincreasediseasetransmission(Brearleyetal.2013,interactionswithclimatechange,increasedhumanpressuresonHemertetal.2014,Priceetal.2019,Wilkinsonetal.2018,naturalsystems,andotherforces(Muhlfeldetal.2014,RahelYoungetal.2017).Thewildland-urbaninterfaceandotherareasandOlden2008).ofincreasedinteractionbetweenhumans,domesticanimals,andwildlifeareespeciallylikelytoleadtoincreasedtransmissionPathogensofdisease(BradleyandAltizer2007,Deemetal.2001,Milleretal.2017,Wilkinsonetal.2018).GiventhesecompoundingPathogensareaseriousrisktofish,game,andwildlifeinthefactors,researchiscurrentlylackingonthefullcomplexityofNation’sforests(Wobeser2007,Wooetal.2006).Inadditiontotheseinteractions(Ryser-Degiorgis2013,Stallknecht2007)directimpactsonindividualsandspecies,diseasecaninteractthatcouldhelpmanagersprepareforprojectedincreasesinwithhuman-causedenvironmentalchangesandalterecosystemsoutbreaksandseverity(Buttkeetal.2021).(Brearleyetal.2013,Daszaketal.2001,HilkerandSchmitz2008,Tompkinsetal.2011).DiseasepathogensaredefinedAnthropogenicDriversofChangehereasanyfungal,bacterial,orviralmicroorganismcausingdysfunctioninstructureorfunctionofthebody(BallouxandvanConnectionandinterconnectionwithinandamonghabitatsDorp2017,Scholthof2007)aswellastrematodeparasitesthatarecrucialforthelong-termpersistenceofnativebiota.cancauselimbmalformationsinanurans(Johnsonetal.2002).Nativespeciesareadaptedtothedisturbanceprocessesmostprominentonalandscape(suchaswildfire),assumingtheyThereareavarietyofwaysthatpathogensinteractwithwildlifeoccurwithinthenaturalrangeofvariability(Johnstoneetcommunities.Endemicorpreexistingdiseasesmaychangeal.2016).Disturbancesassociatedwithhumanlanduseandinrateorintensity(Priceetal.2019,Rachowiczetal.2005).development(includingwildfiresuppression),however,haveDiseasesthathavenotpreviouslybeenseeninapopulationorextensivelyalteredtheavailabilityandpatternsofhabitatsspeciesmayarriveviatransmissionfromanothergroup,orbyatlandscapescales,leadingtoextirpationofsomespecies.evolvingintoanewpathogen(Daszaketal.2000,Kocketal.Vulnerabilitytoextinctioncurrentlyexistsforhundredsof2010,Rachowiczetal.2005).Thesenewpathogensvaryinspecies,farbeyondthoselistedundertheESA(Harrisetal.therateoftransmissionandspreadwithinandbetweenwildlife2012).Theexistinglandscapewilllikelybefurtherstressedpopulations(Gallanaetal.2013,VanHemertetal.2014,seetheincomplexwaysastheeffectsofclimatechangeprovideansidebarHerpetofaunaDiversityandThreats).Thesepatternsareadditionallayerofstressonnativeecosystems(Mantyka-influencedbyhumanactivitiessuchaslandmanagementandPringleetal.2015).Thissectionprovidesmodelingworktheinteractionsofdomesticatedandwildanimals(BradleyandaddressingtheeffectsoflanduseandclimatechangeonnativeAltizer2007,Brearleyetal.2013,Daszaketal.2001)becausebiodiversity,individuallyandtogether.ofthepotentialfordiseasetransmissionbetweenthesegroups(Daszaketal.2000,Milleretal.2017,Pedersenetal.2007).TheLandUseexistenceofmultiplehosts,parasites,andlifestages,however,cancomplicatetransmission(Rachowiczetal.2005,VanHumanuseanddevelopmentoflandscapesdirectlyaffectbothHemertetal.2014).terrestrialandaquaticbiodiversity.Driversofbiodiversitylossassociatedwithhumanactivitiesincludelong-termlandTheeffectsofdiseaseonwildlifecanrangefrommildtocoverchange,degradedandhomogenizedwildlifehabitats,catastrophic.Althoughsomeindividualsmayreproduceandliveandthecreationofpathwaysforintroductionofnonnativelongliveswithfewsymptomsofadisease,thesecarrierscanspecies(Allan2004,Flatheretal.1998,Howardetal.2020,beresponsibleforextensivediseasetransmission(Artoisetal.10-16FutureofAmerica’sForestsandRangelandsRegetz2003,Wilcoveetal.1998).Toassesswherefuture(seetheLandResourcesChapter,alsoBealeandJohnsondevelopmentandexpansionmaycauseincreasingstresson1998,Hjerpeetal.2020,Kirketal.2012,Radeloffetal.nativeecosystems,weexploredchangingpatternsofthreekey2018).Suchexpansionthreatensnativeecosystemswiththemesrelatedtolandusechange:humanpopulationgrowthhabitatfragmentationanddecreasesinnativespeciesdiversity.andurbandevelopment;agriculture;andenergydevelopmentIndirecteffectsofdevelopmentincludeincreasedamountsandmining.ofimpervioussurfaces,roads,noise,andlight.ImpervioussurfacesandroadsincreasesedimentationandpollutantrunoffForeachofthethemes,wecreatedstressindicesforHUC10intostreamsandmodifyregionalhydrology.RoadsalsoleadwatershedsthroughouttheconterminousUnitedStatesusingtodirectmortalityofanimals,disruptdispersalandmigration,principalcomponentanalysis(PCA)ofvariablesshowninandserveaspathwaysforinvasivespecies(Bennett2017,table10-2,usingtheprcompfunctioninthestatspackageinRRegetz2003,SiemersandSchaub2011).Anthropogenic(RCoreTeam2021).PCAisadata-reductiontechniquethatnoiseandlightpollutionhavealsobeenlinkedtodeclinesinsimplifiesdatasetswithmany,sometimes-correlatedvariables,wildlifeandalterationsinbehavior(Barberetal.2010,Carral-intofewerdimensions(calledprincipalcomponents)todrawMurrietaetal.2020,KerthandMelber2009,Shannonetal.outtrendsandpatterns—inthiscase,tomoreclearlyshow2016,SiemersandSchaub2011).variationinthecombinationofstressorsamongwatersheds.WeperformedPCAonvariablesassociatedwitheachoftheThestressindexusedforpopulationgrowthandurbanthemesindividuallyandforallthevariablestogether(thedevelopmentfocusesonhousingdensity,population,andaggregateindex),providingstressindicesforeachHUC10roads(figure10-19a).PCAforthesevariablesreducedwatershed,showninfigure10-19.Resultsallowmorerefinedthedatatothreeprincipalcomponents.Thefirstprincipaldiscussionofwatershedthreats,examiningthemajordriverscomponent,accountingfor47percentofthevariationamongandhowtheyvarybyregion.watersheds,isheavilyweightedtowardpopulationdensityandroads,identifyingwatershedsnearcitiesandlargePopulationGrowthandUrbanDevelopmentmetropolitanregions.Watershedsaffectedbyhumanactivityoutsideofcities,namelyroadsinsteepareasandcrossingTheU.S.populationisprojectedtogrowbetween24and44streams,explain18percentofthevariation.Roadsfragmentpercentfrom2010through2070underintermediatescenarioshabitatbycreatingbarrierstoaquaticorganismpassage,and(SharedSocioeconomicPathways1,2,and4;Wearandleadtoincreasedsedimentationofwaterways.Thesehigh-Prestemon2019).AlthoughmuchofthatgrowthisexpectedstresswatershedsoccurfrequentlyinthesouthernGreattobecenteredonmetropolitanregions,thefastestareasofPlains,centralArizona,andmountainousareasacrossthedevelopmentareontheurbanfringe,aslargemetropolitanUnitedStates,withparticularlyhighstressintheAppalachiansregionsexpandtheirexurbanandwildlandinterfaceareasstretchingfromwesternNorthCarolinatoPennsylvania.Table10-2.Variablesanddatasourcesusedinstressindices.VariablesDatasourcesUrbandevelopmentandpopulationgrowthDevelopedlanduse30-mNLCD2011LandCover(2011Edition,amended2014);NationalGeospatialDataAssetHousingdensity(populationperkm2)LandUseLandCoverPopulationchangeSILVISLab,Dept.ofForest&WildlifeEcology,UniversityofWisconsin-Madison(2017)PopulationdensityRoaddensityU.S.CensusTIGER2015RoadsNationalGeodatabase;USGS2018QuarterlyNationalRoadstreamcrossingsHydrographyDatasethigh-resolution(1-to-24,000orbetter)streamcoverageRoadsonsteepslopesAgricultureCultivationongentleslopes30-mNLCD2011LandCover(2011Edition,amended2014);NationalGeospatialDataAssetLandUseLandCoverCultivationonhighlyerosivesoilsUSGS7.5-minute(~30-m)NationalElevationDatasetMeandepositionofN,dryNationalCooperativeSoilSurveyWebSoilSurvey~4-kmNationalAtmosphericDepositionProgram(2018).TotalDepositionMaps,v2018.01.OilwellsEnergydevelopmentandminingPipelinedensityHomelandInfrastructureFoundation-LevelData(2018).Retrievedfromhttps://hifld-geoplatform.opendata.arcgis.com/datasets/oil-and-natural-gas-wells/data.Downloaded3Dec2020.NLCD=NationalLandCoverDatabaseNationalPipelineMappingSystem(2004).U.S.Dept.ofTransportation.PipelineandHazardousUSGS=U.S.GeologicalSurveyMaterialsSafetyAdministration.Washington,DC2020ResourcesPlanningActAssessment10-17Figure10-19.Landusestressatwatershedscalesfrom(a)populationgrowthandurbandevelopment;(b)agriculturalexpansion;(c)densityofmines;(d)densityofpipelines;(e)mining/energy;and(f)aggregatestressacrossallsectors(atHUC10scale).Higherscoresindicategreaterstress.Thethirdprincipalcomponent,explaining14percentoftheheavyconcentrations.Thesecondprincipalcomponent,variationinthedata,representswatershedswithnewresidentialwhichisalmostentirelycomposedofwatershedswithoutdevelopments,reflectingtrendsinurbanizationaroundcities,cultivatedcropsbutwithhighlevelsofnitrogendeposition,andforrapidlygrowingurbanareas(e.g.,southernCalifornia,explains21percentofthevariationinthedataandidentifieswesternWashingtonandOregon,centralArizona,Coloradothedownstreamimpactsofagricultureonwatersheds.TheFrontRange,centralTexas).Thisfactoralsocapturesgrowthtwoprincipalcomponentstogetherexplain95percentoftheinruralareas,suchaspartsoftheWasatchRange,RockyvariationinthedataandprovideafullerdescriptionofriskMountains,andAppalachianMountains,whereamenity-driventowatershedsassociatedwithagriculture(figure10-19b),growthhasledtoexpansionofhousinginthewildland-urbannamelythosewithagricultureinthewatershedandthoseinterface,withsignificantimpactsonwildlifehabitat.thatexperiencetheindirecteffectsofrunofffromupstreamwatersheds.Agriculture-relatedstressishighthroughouttheAgricultureGreatPlains,MississippiRiverbasin,easternWashington,andcentralCalifornia.Inhuman-dominatedecosystems,establishedagriculturalareascanhostanabundanceofspecies,includingpollinatorsEnergyDevelopmentandMining(Devictoretal.2008,Kraussetal.2003,Westphaletal.2003),butagriculturalexpansionalsoconvertscomplexStressonwatershedsfromminingactivityderivesfromlandscapesintosimplemanagedecosystems,intensifiesacidrockdrainage,increasedmovementofpollutantssuchresourceuse,andincreasespollutantsviafertilizerandasmetalsulfidesfollowingheavyrainfallandfloods,andpesticideapplication(Donaldetal.2001,Dudleyandimpactsonwildlifepopulationsandmovements.WatershedsAlexander2017,RobinsonandSutherland2002,Tscharntkecontainingactiveorabandonedminesareaffectedbyetal.2005).Thestressindexforagricultureusesvariablescomplexinteractionsofsurfaceandsubsurfaceflowsthatrelatedtocultivation,erosionpotential,andnitrogenintroduceacidityandmetalstothereceivingstream.Thesedeposition(table10-2).ThePCAresultsforagricultureinfluencesmayalsoemanatefromnaturalsourcesinthedonotdifferentiatewatershedtypesasclearlyastheunderlyingbedrock.Eveninareaswithoutactivemining,developmentPCA,perhapsbecausethereismorevariationsomeecosystemshavenotcompletelyrecoveredfromindegreesofdevelopmentthanagriculture.Thefirstminingthattookplaceinthe19thcenturyandcontinuesprincipalcomponentcaptures74percentofthevariationtoimpactstreamchannels,sedimentation,andreleaseofamongwatershedsandmostlydistinguisheswatershedstoxicchemicals(Schmidtetal.2012,Wohl2006,Wohletwithheavyconcentrationsofagriculturefromthosewithoutal.2015).Short-termimpactsrelatedtotheconstructionof10-18FutureofAmerica’sForestsandRangelandsSoutheasternCrayfishDiversityandThreatsCrayfisharefoundinawiderangeofhabitats,includingourabilitytoassesscrayfishstatusandmanagecrayfishpermanentandseasonalriverineandlacustrinehabitats,populations(Barnett2017,LoughmanandFetzner2015,freshwatercavesandsprings,andterrestrialburrows.Mooreetal.2013).Crayfishplayasignificantroleintheseecosystemsbyprocessingdetritusandmacrophytes,whichincreasesCrayfishimperilmentisoftenattributedtosmallrangetheavailabilityofnutrientsandorganicmattertoothersizesanddegradationofhabitatsthroughpollution,urbanorganisms;diggingburrows,whichmanipulatesanddevelopment,anddams/watermanagement(Crandallmobilizessubstrate,makingnutrientsandhabitatavailableandBuhay2008,Richmanetal.2015);however,theretootherstreamorganisms;andservingaspreyfor,orisapaucityofstudiesthatdirectlyassessthesethreatstopredatorson,numerousaquaticanimalspecies,especiallysoutheasterncrayfishes.Existingstudiesassessingdams/somegamefishessuchasbassandcatfish(Holdich2002,watermanagementshowthatsmalldamsshifttherelativeReynoldsetal.2013).Thus,crayfishinfluencemultipleabundanceofstreamcrayfishes(Adams2013,Barnettaspectsofecosystemstructureandfunction.TheyalsoandAdams2021,Barnettetal.2022)andlargedamsserveasaprofitableandpopularfoodresource(LarsondecreasethedensityanddiversityofstreamcrayfishesandOlden2011).whencomparedtostreamswithoutdams(Barnett2019,BarnettandAdams2021,Barnettetal.2022).DamshaveGlobally,crayfishreachtheirhighestlevelofdiversityalsocausedgeneticfragmentationofstreamcrayfishintheUnitedStates(~400speciesandsubspeciesversuspopulations(Barnettetal.2020,BarnettandAdams2021).500+intheworld[65percent])(Tayloretal.2019).InSimilarlyfewstudieshaveassessedtheimpactsofthreatstheUnitedStates,crayfishdiversityreachesitspinnacletocrayfish—theComprehensiveEvergladesRestorationintheSoutheast(~200species;notablyTennessee,Planistheonlywell-knownmajorrestorationinitiativeAlabama,andMississippi)(Richmanetal.2015).Crayfishthatfocusesoncrayfishes(Tayloretal.2019).Becausehaveahighlevelofendemism,withovertwo-thirdsofoftheirimportantroleasecosystemengineersandbothCambaridaespecies(thefamilyof99percentofNorthpredatorandpreyinaquaticandterrestrialecosystems,Americancrayfishes)endemictotheSoutheasternUnitedcrayfishconservationalsoprotectsotherorganismsStates(Simon2011).Crayfishareimperiledovermuchofconservationconcern,aswellascriticalecosystemoftheirrange,with50percentofallU.S.speciesatsomefunctions(Boyleetal.2014,Reynoldsetal.2013,Wolffetlevelofconservationconcern(Tayloretal.1996,2007)al.2015).and22.5percentlistedinthreatenedorhigherconcerncategories(Tayloretal.2019).AlthoughinterestinZanethiaC.Barnett,USDAForestService,SouthernResearchcrayfishconservationisrapidlygrowing,basicbiologicalStationandecologicalinformationislacking,severelyhinderingwellsandpipelinesincludeincreasedturbidity,modificationCanadaovera15-yearperiod.IntheUnitedStates,thereofaquatichabitats,andopportunitiesforfuelsandchemicalswere614pipelineincidentsofsomekindreportedin2019toenterthesystemduringtheconstructionstage(Maloney(FracTracker.org,accessed26January2021).Ananalysisetal.2018,ReidandAnderson1999,Reidetal.2003).ofabout7,000U.S.onshoreliquidpipelineincidentsOilandgaswells,aswellasdevelopmentandroads,havethatoccurredfrom1985to2012found5.5percentofallalsobeenshowntoalterwildlifemovementsandmigrationincidentsweretriggeredbynaturalhazards,28percentledtopatternsacrossbroadspatialscales(Jakesetal.2020).Long-releasesintowaterbodies,andmorethan20percentresultedtermimpactsofoilandgasdevelopmentincludechannelinfires(GirginandKrausmann2016).incisionandlateralmovement,alongwiththepotentialforcatastrophicimpactsfromafuturespill.PipelinesThePCAforenergydevelopmentandminingaggregatesmightmakehundredsorthousandsofstreamcrossingsthemining,well,andpipelinedataintoonethreatindex,andintersectawidevarietyofhabitats(Levy2009),withidentifyingpartsofthecountrythathavesignificantlymorethepotentialforspillstomovecontaminantsthroughlargeenergyandminingactivitythantherestofthecountry.riversystems.EvensmallreleasesofoilandgashaveMiningiswidespreadthroughouttheWest,theOzarks,partsbeenshowntoinjureandkillwildlife(Ramirez2010,oftheGreatLakes,andtheAppalachiansstretchingintotheRamirezandMosley2015).Levy(2009)foundthatthereNortheast(figure10-19c),whereasthedensityofpipelineswere762pipelinefailuresperyearonaverageinAlberta,increasestowardtheGulfCoastofTexasandLouisiana,2020ResourcesPlanningActAssessment10-19althoughpipelinesalsocrisscrossmuchoftheEasternchangesintotalannualprecipitationvarygeographically.InUnitedStates(figure10-19d).Themixofminesandpipelinesaddition,climatechangeisprojectedtocontinuealteringnaturalleadstostressrelatedtoenergydevelopmentdistributeddisturbancessuchaswildfire(seetheDisturbanceChapter).throughouttheUnitedStates,withhotspotsoccurringintheThetotalareaofthecountryaffectedbywildfirehasincreasedWest,Ozarks,andSoutheast(figure10-19e)—areasthathaveannuallyandthisincreaseisprojectedtocontinueunderclimateexperiencedimpactsonterrestrialandaquaticspecies(Allertchange(Westerling2016).Wildlifehabitatwillbeaffectedbyetal.2009,Jakesetal.2020).Ofnotearethelargepartsofthetheinteractionofchangesinclimateandnaturaldisturbancescountrywheredataaremissing.Availabilityofdataonmines(Weiskopfetal.2020).andwellsislimited,collectedinconsistentlybyStates.LackofavailabilityofdataisaseriouslimitationtoassessingtheimpactsModelInputstheenergysectormighthaveonwatershedsandwildlife.WeexplorethepotentialeffectsofclimatechangeonwildlifeAggregateIndexofLandUse-DrivenStresshabitatatthescaleoftheconterminousUnitedStatesusingthe10climateprojectionsdevelopedfortheRPAAssessment,twoWecalculatedanaggregatePCAusingallthevariablesinthedisturbancetreatments(firesuppressionandnofiresuppression),individualindices.ThefirstthreeprincipalcomponentsofthisandtheMC2dynamicglobalvegetationmodel.TheScenariosaggregateindexcumulativelyaccountforabout55percentoftheChapterdescribesthedevelopmentoftheclimateprojectionsvariationinwatershedstressors,withtheindividualcomponentsusingthetwoclimatescenariosfromtheIntergovernmentalaccountingfor31,14,and10percentofvariationinthedata,PanelonClimateChange(RCPs4.5and8.5,representingrespectively.Theaggregateindexshowsthestarkdifferenceinlowerandhighatmosphericwarming,respectively)andfivepressuresfacedbyeasternandwesternwatersheds.AlthoughclimatemodelsidentifiedforuseintheRPAAssessment.miningmighthavesignificantimpactsonthewatershedsinClimateprojectionsunderRCP4.5and8.5weredrawnfromwhichitoccurs,energydevelopmentisnotwidespreadenoughthedownscaledclimatedatasetforeachofthefiveclimatetoscorehighatalargeregionalscale,especiallycomparedtomodels,resultingin10uniqueclimateprojections.Thecoresetimpactsfromdevelopmentandagriculture.Thelargestsourceofoffiveclimatemodelswereselectedfromtheavailablemodelsvariationbetweenwatershedscomesfromnitrogendepositionbasedontheirabilitytocapturetherangeoftemperatureandandroads;collectively,theyaffectmostofthewatershedsintheprecipitationchangeatmid-andend-centuryunderRCP4.5EasternUnitedStates(figure10-19f).High-riskwatershedsinand8.5(table10-3,alsoseetheScenariosChapterformoretheWesternUnitedStatesaremainlynearthelargemetropolitaninformation).regions.ThePacificCoastandRockyMountainRegionsgenerallyscorelowonaggregatestress,butincreasedstressFuturevegetationbiomassandshiftsinvegetationtypeswereexistsinthepopulationandagriculturalcentersofWashington,assessedbythedynamicglobalvegetationmodelMC2—aIdaho,andCalifornia,andpocketsoftheRockyMountainsthatmodelthatprojectsvegetationresponsetochangesinareexperiencingrapidpopulationgrowth.temperature,precipitation,anddisturbance(fire,drought)basedonbiogeographicandbiogeochemicalprocessesinecosystemsClimateChange(Bacheletetal.2016,Klemmetal.2020).Twodisturbancetreatments—firesuppressionandnofiresuppression—wereClimatechangeisaffectingterrestrialandaquaticvertebrateanalyzedusingtheMC2modelundereachofthe10climatespeciesintheUnitedStates,resultinginlarge-scaleshiftsintheirprojections,resultinginatotalof20plausiblefutureprojections.rangeandabundance(Howardetal.2020,Liptonetal.2018).WildfireisadisturbanceofconcernbecauseitcanchangeaAtthescaleoftheconterminousUnitedStates,annualaveragelandscapeinashortperiodoftime,incontrastwithgradualtemperaturehasincreased1.8°F(1.0°C)overtheperiod1901changesinmeanclimate.The“nofiresuppression”disturbanceto2016andisprojectedtorisebyabout2.5°F(1.4°C)byscenariodecreasesthefire-returnintervalandallowsfora2050underallplausiblefutures(USGCRP2017).Projectedpotentialfullrangeofchangesinfuturefiredynamics,whereasTable10-3.Fiveclimatemodelsselectedtoreflecttherangeofthefullsetof20climatemodelsintheyear2070.EachmodelwasrununderRCP4.5andRCP8.5,providingarangeofdifferentU.S.climateprojections.ClimatemodelLeastwarmHotDryWetMiddleMRI-CGCM3HadGEM2-ESIPSL-CM5A-MRNorESM1-MCNRM-CM5InstitutionMeteorologicalResearchMetOfficeHadleyInstitutPierreSimonNorwegianClimateLaplace,FranceNationalCentreofCenter,NorwayInstitute,JapanCentre,UnitedKingdomMeteorologicalResearch,FranceRCP=RepresentativeConcentrationPathwaySource:JoyceandCoulson2020.10-20FutureofAmerica’sForestsandRangelandsthe“firesuppression”scenariocanextendthemeanfire-Figure10-20.TerrestrialClimateStressIndex(TSCI)scoresrankedbyreturnintervalinsomeecosystems(Sheehanetal.2015).Thepercentile.HighstressisaTCSIscoregreaterthanthe80thpercentile(darkconterminousclimateandMC2basedatawereconvertedtoblue).Projectionsshownareunderthehotmodel(toptworows)anddryequal-areagridsat4-kmresolution.model(bottomtworows).ProjectionsincludetwoRCPscenarios(RCP4.5and8.5)andtwodisturbancetreatments(firesuppression:leftcolumn,andnoTheMC2modelassessestheeffectsofclimateanddisturbance;firesuppression:rightcolumn).historicalvegetationisassumedtobepotentialvegetation.LandusechangewasnotincludedintheMC2runs,meaningthatFiresuppressionNofiresuppressiontheinevitablefuturelandusechangelinkedtosocioeconomicchanges(seetheLandResourcesChapter)wasnotanalyzedHothere.Areasofopenwater,developed,andbarrenlandcover—asRCP4.5definedbytheUSDANaturalResourcesConservationService(Homeretal.2020)andapproximating11percentoftheHotconterminousarea—wereremovedfromtheanalysis.ChangesRCP8.5inlandusewilllikelyresultinaddedstressonterrestrialandaquaticecosystemsintheUnitedStatesasurbanlandscapesDryexpandandruralrefugesdisappear.WeaddresstheimplicationsRCP4.5ofthisomissioninourcaveats.DryTerrestrialClimateStressIndexRCP8.5TheTerrestrialClimateStressIndex(TCSI)isusedtoRCP=RepresentativeConcentrationPathway.simultaneouslyexplorechangesinannualmeantemperature(°C),totalannualprecipitation(cm),andannualvegetationprojectionssuggeststhatalthoughtherearecommonareasofproduction(gramscarbonperm2)betweenhistorical(1951highstressacrossthefourtreatments(AppalachianMountainsinto2000)andfuture(2050to2099)periodsforeachofthetheSouthRegion),individualRCPsanddisturbancetreatments20projections.DeviationsinlocationandvariancebetweencaninfluencethelocationofhighstressacrosstheconterminoushistoricalandfuturedistributionsarecapturedbycalculatingUnitedStates.Bhattacharyyadistance(Bhattacharyya1946),wherelargerdistancesequatetolargerdifferencesbetweenthehistoricandThenorthernareaoftheRockyMountainRegionisprojectedfutureperiods.WeusetheBhattacharyyadistancesastheTCSItobeinhighstressunderthefiresuppressiontreatment(bothscorestoranktherelativedifferences.WedefinehighstressRCPs);however,fewgridcellsareprojectedtobeinhighstressasthe20percentofcellswiththehighestTCSIscore(mostundernofiresuppression(bothRCPs).Historicalfireregimesindifferencebetweentimeperiods)foreachofthe20projections,thisareahaverestrictedtheadvanceofwoodyspecies.Withoutsimilartomanyclassificationsofdrought.Thisindexthereforefuturefiresuppression,wildfirewillcontinuetominimizewoodydescribesthemagnitudeofdeparturesfromhistoricalconditionsspeciesadvances.Theadditionoffire-suppressiontreatments,andidentifieswherefuturehighstressisprojectedacrossthehowever,couldenabletheadvanceofwoodyspeciesandresultconterminousUnitedStates.Explorationofanindividualinhigherfuturestress(alsofoundbyKlemmetal.2020).projection(e.g.,thehottestorthedriestofthesuiteofWildfiremanagementmayneedtoconsidertheshiftingchangesprojections)highlightsareaswherethatparticularstressormayinfireregimesunderclimatechangeandthefutureroleofresultinchallengestonaturalresourcesunderthoseplausibleprescribedfireunderthosechanges.futures,whereastheTCSIbasedonallprojectionsportraysconsistencyinprojectedfuturehigh-stresslocationsacrosstheconterminousUnitedStates(seefollowingsection).HighTerrestrialClimateStressAreasUndertheHotProjectionsThehotclimatemodelwasrunforRCP4.5andRCP8.5,underthetwodisturbancetreatments(firesuppression,nofiresuppression)toidentifyareasofhighstressunderahotfuture(figure10-20).HighstressisdefinedasaTCSIvaluegreaterthanthe80thpercentile(i.e.,top20percent).Becausethesescoresarerelativetoeachprojection,theshiftsdemonstratehowstresschangesdependingontheRCPscenarioanddisturbancetreatment.Comparingtheresultsacrossthesefourhot-model2020ResourcesPlanningActAssessment10-21AnoticeabledifferencebetweentheRCP4.5and8.5scenariosFigure10-21.ThecumulativenumberofprojectionsthatidentifyfuturehighoccursinthesouthwesternareaoftheRockyMountainRegion.stressforeverycell,basedonthesetof20projections.Barrenarea,openwater,HighstressisfoundinthissouthwesternareaunderRCP4.5anddevelopedareas(whiteonthemaps)arenotincludedintheanalysis.(bothdisturbancetreatments)butnotunderRCP8.5(bothdisturbancetreatments),suggestingthatatmosphericwarminghasagreaterinfluenceonstressintheseareasthanfire-suppressiontreatments.HighTerrestrialClimateStressAreasUndertheprojectionsthatidentifyfuturehighstressineachcell,outofDryProjectionsthe20totalprojections.FortheconterminousUnitedStates,wedefineareasofconcentratedstress(hotspots)asoccurringThedryclimatemodelwasrunforRCP4.5andRCP8.5,where10ormoreprojectionsidentifyhighstress.underthetwodisturbancetreatments(firesuppression,nofiresuppression)toidentifyareasofhighstressunderadryAreasofconcentratedhighstressoccurinallRPAregions.future(figure10-20).ComparingtheresultsacrossthesefourHigh-elevationareasareconsistentlyrankedashighprojectionssuggeststhatalthoughcommonareasofhighstressstress,includingthemountainsofCalifornia,Oregon,arevisibleacrossthefourprojections(northeasternareaoftheandWashingtoninthePacificCoastRegion;theRockyNorthRegion),individualRCPsanddisturbancetreatmentscanMountains(MontanathroughColorado)intheRockyinfluencethelocationsofhighstressacrosstheconterminousMountainRegion;areasintheAppalachianMountainsandUnitedStates.OzarksintheSouthRegion;andnortheastmountainsintheNorthRegion.ScatteredaridlandsinsouthernArizonaandThehigh-stressprojectionsunderthedrymodelaresimilartoNewMexicointheRockyMountainRegionconsistentlytheresultsofthehotmodelfortheRockyMountainRegion:showhighstress.AreasineasternOklahomaandpartsofhighstressinthenorthernpartoftheregionisprojectedforbothTexas,andcentralMinnesotaalsoseehighstress.RCPsunderfiresuppression(coveringalargerareathanunderthehotmodel)andrelativelylowstressisprojectedundernoStressProjectionComparisons:NationalForestsandU.S.firesuppression.ChangesinfireregimesunderclimatechangeNationalParkServiceLands,ComparedwithAllOthermaybeanimportantconsiderationforresourcemanagementLandsAcrosstheUnitedStatesintheseareas.AllfourprojectionspredictfuturehighstressinthenortheasternareaoftheNorthRegion.IncontrasttoLandmanagementunderFederalownershipincludesavarietyofthehot-modelprojection,wherehighstresswasseenintheobjectivesincludingbothconservationandresourceextraction,AppalachianMountains(extendingintothenortheasternbuttheselandsarelessvulnerabletodevelopmentorlandareabutnotincludingMaine),highstressinthedrymodelconversioncomparedwithotherlandownerships.Federallyintensifiesinthefarnortheasternareaacrossallfourownedlandsthereforehavethepotentialtoplayanimportantprojections.Furtherexplorationofdroughtinthisareamayroleasclimaterefugiawhenconsideringclimatevulnerability.bevaluableforlocalresourceplanning.AlsocommontoTobetterunderstandhowclimatechangemayaffectFederalallfourprojectionsistherelativelylargeareawithouthighlandsandtheirpotentialtoserveasclimaterefugia,wecomparedstressinthesouthernpartsoftheSouthRegion.StressisstillstressprojectionsforNationalForestSystem(NFS)andU.S.evident,butwhencomparedtootherareas,thisrelativelyNationalParkService(NPS)landswithstressprojectionsforallwetregionisprojectedtohavefewareasofhighstressunderotherlands(bothpublicandprivate,butnotnecessarilysetasidethedry-modelprojections.asprotected)intheconterminousUnitedStates(figure10-22).Consistentwiththehot-modelprojections,areasofhighLookingattheTCSIresultsforNFSandNPSlandsshowselevationareprojectedtoexperiencehighstressunderthehighstressareasacrossthesenetworks(figure10-22,top).dry-modelprojections.ThesecommonareasofhighstressConcentratedhighstressisseenintheRockyMountainandincludethemountainsthroughoutthePacificCoastandPacificCoastRegions,notablythecentral/southernRockyRockyMountainRegions.HigherelevationsintheeasternpartoftheconterminousUnitedStatesappeartoexperiencemorestressunderhotprojectionsthandryprojections.HighTerrestrialClimateStressTrendsAcrossProjectionsGridcellsthatareconsistentlyrankedashighstressacrosstheprojectionsdenoteareasthataremostlikelytoexperiencehighstressinthefuture,basedonthissuiteofplausiblefutures.Figure10-21showsthenumberof10-22FutureofAmerica’sForestsandRangelandsFigure10-22.ThenumberofcumulativeprojectionsthatidentifyfuturehighImplicationsofTerrestrialStressstressfor(top)NationalForestSystemandU.S.NationalParkServicelands,and(bottom)allotherlands,basedonthesetof20projections.Climatechangehasalreadyhadnegativeimpactsonmanythreatenedwildlifespecies(Pacificietal.2017),anditwilllikelyNFS=NationalForestSystem;NPS=U.S.NationalParkService.continuetoadverselyaffectmanymorespeciesasprojectedincreasesintemperatureandvariationinprecipitationleadMountains,northwesternUtah,partsofMontana,andtheSierrastochangesinvegetationandfireregimes.AsinourpreviousinCalifornia.Highstressonallotherlandsoccursasisolatedassessments,theseresultsalsosuggestthatthehistoricalareasofhighstressacrossthecountryandconcentratedintheinfluenceoffireonvegetationisanimportantconsideration.northeasternareaoftheNorthRegion,southernTexas,andtheTheeffectofachangingclimateandachangingfireregimeCoastRangeinOregon(figure10-22,bottom).differsdependingonthemanagementofwildfire,particularlyWeaveragedTCSIforall20projections(1)acrossNFSandwherefireregimehasbeenamajorinfluenceinsustainingaNPSlandsand(2)acrossallotherlands(notpartoftheNFSorspecificvegetationtype(e.g.,grasslands).Large,high-severityNPS)andtestedfordifferencesusingapairedt-test.FuturestressfirescanleadtomoreheterogeneouslandscapesthatprovideissignificantlygreaterforNFSandNPSlandsthanforallotheramosaicofhabitattypesfacilitatinggreaterbiodiversity(e.g.,lands,basedonchangesinclimateanddisturbance(p-valuegrasslandbirds;Fuhlendorfetal.2006).However,thereare<0.0001;t=5.07,df=19).manyfeedbackcyclesassociatedwithfireandconfoundedwithBecauseelevationisconfoundedwithtemperature,futureclimatechange.Forexample,cheatgrass(Bromustectorum),anwarmingtemperaturesmeanthathigherelevationareasareinvasiveplantspeciesofparticularconcernintheGreatBasinmorelikelytobeinhighstress.NFSandsomeNPSlandsowingtoitsnegativeimpactonwildlifespeciesinsagebrushlargelyexistinthemountainousregionsofthecountryathigherecosystems,hasbeenshowntohaveapositivefeedbackelevationsthanotherlands(meanelevationof1542mversuscyclewithfire(Coatesetal.2016).Themountainpinebeetle709m),adrivingfactorforthesignificantlyhigherstressfound(DendroctonusponderosaeHopkins)isanotherexampleintheintheselands.However,thecorrelationbetweenelevationandRockyMountainswherewarmingtemperatureshavealteredthenumberofprojectionsidentifyingacellinhighstressacrossthebeetle’slifecycle,leadingtoemergenceofmoreindividualstheconterminousUnitedStatesisweak(r=0.15),suggestingsimultaneously,whichinturnleadstomoresuccessfulattacksthatotherfactorsincludingwildfiresuppressionalsocontributeandmoredeadtreesthataremorelikelytoresultinlargecrownsubstantiallytothisresult.fires(LoganandPowell2001).Thesecascadingeffectsthreatentrophicinteractionsthathaveadaptedtohistoricalnormsandarerapidlychangingatapacewildlifespeciesmaynotbeabletokeepupwith.Federallandsareexpectedtoserveasfuturerefugiaifsurroundinglandsareconvertedtootherlanduses.Althoughourstudydidnotincorporatelanduseasafactoraffectingvegetation,ourfindingthatNFSandNPSlandsareprojectedtoexperiencehigherfutureclimatestressthanallotherlandssuggeststhattheabilityoftheselandstoserveasrefugiamaybelimitedbyclimatestress.Nevertheless,Federallandsmayofferimportantlandscapesthroughwhichwildlifecandisperseinresponsetochangingenvironmentalconditionsresultingfromclimatechange.Weidentifiedseveralareaswhereamajorityoftheplausiblefuturespredicthighstress:mountainsinthePacificCoast,RockyMountain,andSouthRegions;largeareasfromNewYorktoMaineintheNorthRegion;andlowerelevationlandsinsouthernNewMexico,southernArizona,Oklahoma,andTexas.Theconsistencyofhighstressintheseareassuggeststhatwildlifemanagerswilllikelyseechangesinwildlifehabitatandwildlifedistributions.Forexample,decreasedrangesforwildlifethatareparticularlyvulnerabletoheatstress,suchasmarten(Martesamericana)andlynx(Lynxcanadensis),mayleadtoassociatedpopulationdeclines(Carroll2007).Otherindirecteffectssuchasincreasedparasiticvulnerabilitycouldalsocontributetopopulationdeclinesinmanywildlifespecies,such2020ResourcesPlanningActAssessment10-23aswinterticks(Dermacentoralbipictus)onmoose(Alcesalces)report,wedescribedthemodelingandmappingofstressorsfrom(Rodenhouseetal.2009).landuseandclimatechange.Here,wecombinelandusestress,futureclimatestress,andbiodiversitydatainordertovisualizeThelocalexplorationofdifferentindividualclimateprojectionsoveralldistributionsofcurrentandfuturerisktoecosystems(leastwarm,hot,dry,wet,middle)mayassistresourcemanagersacrosstheconterminousUnitedStates.Futureclimatestressinidentifyingthesignificantimpactsonwildlifeandwildlifeinthesesectionsistheaggregateofalltheclimatepredictionhabitatwithrespecttoaparticularplausiblefuture(Lawrencemodels(n=20)thatidentifiedaspecificcellashighstress,asetal.2021).Thereisvalueinexaminingindividualprojections,describedaboveintheTerrestrialClimateStressIndexsection.asvegetationsensitivitytochangesinclimatevariesacrosstheconterminousUnitedStates.InourexaminationofthehotandAnthropogenicStressorsdryprojections,itwasapparentthatatmosphericwarming(RCP4.5versusRCP8.5)canhavemoreinfluencethandisturbanceOurassessmentofanthropogenicdriversofchange(describedtreatmentsonhigh-stressprojectionsandviceversa.Thenotableindetailabove)capturescurrentstressorsonthelandscapeexampleisfiresuppressioninthenorthernpartoftheRockyresultingfrom(1)landuseandassociatedhumanactivitiesandMountainRegion,wherewoodyspeciesexpandedunderfire(2)changingenvironmentalconditionsresultingfromclimatesuppressionbutnotundernofiresuppression.Assessingthechange.ThelandusestressorassessmentidentifiedtheEasternpotentialchangesinwildfireregimeswillbeimportantinUnitedStatesashighlyvulnerabletoseveralindividualstressors,planningnaturalresourcemanagementinthefuture,aswillandwithgreateroverallstressthantheWesternUnitedStates.tailoringstrategiestothecircumstancesthatcharacterizevariousIncontrast,severalareasofhighstressinresponsetofuturelandscapes.GiventhelargerangeofhabitattypesidentifiedtoclimateconditionswereidentifiedintheWesternUnitedStates.beunderhighstress,climatechangewilllikelybeanimportantTovisualizetheinteractionbetweentheseformsofecosystemcomponentoffuturehabitatmanagementplans,specificallystressrepresentingcurrentandfutureconditions,wecombinedaddressingpossiblemitigationstrategiesthataretailoredtothedatasetsusingthePlustoolinArcGISPro2.8.3.Combiningindividualconservationneeds.thesetwoindicesallowsustoseewherebothidentifysimilargeographicpatternsandwhichareasoftheconterminousUnitedCombiningStressorsStatesarelikelytoexperiencecompoundingstressors.TheresultingmapidentifiesareasofhighcombinedstressorsintheInteractionsamongindividualstressorsthataffectecosystemNorthRegion,alongwithareasofconcentratedcombinedstresshealthcancompoundvulnerabilityofalreadyalteredecosystemsinmuchofColorado,southernTexas,andtheSierraNevadasofandthebiodiversitytheysupport.IntheprevioussectionsofthisCalifornia(figure10-23).Figure10-23.Stresspresentedasanindexfor:futureclimatevulnerability—definedasthenumberofclimatemodelsthatidentifiedanindividualcellashighstress(mapinupperleft);currentaggregatelanduseimpacts(mapinupperright);andacombinationofthetwoindicesdevelopedusingthePlustoolinArcGISPro2.8.3(mapinlowercenter).10-24FutureofAmerica’sForestsandRangelandsFigure10-24.Hotspotswithbothhighterrestrialbiodiversityandalikelihoodofhighfuturestress.Overlayinganindexoffutureclimatechange(mapinupperleft)—definedasthenumberofclimatemodelsthatidentifiedanindividualcellashighstress—onterrestrialbiodiversity(mapinupperright)resultsinamapthatidentifieshotspotswithbothhighterrestrialbiodiversityandalikelihoodofhighfuturestress(mapinlowercenter).Futureclimatestressandsourceinformationforbiodiversitymapdescribedinpriorsectionsofthechapter.Figure10-25.Hotspotswithbothhighaquaticbiodiversityandalikelihoodofhighfuturestress.Overlayinganindexoffutureclimatechange(mapinupperleft)—definedasthenumberofclimatemodelsthatidentifiedanindividualcellashighstress—oncurrentaquaticbiodiversity(mapinupperright)resultsinamapthatidentifieshotspotswithbothhighaquaticbiodiversityandalikelihoodofhighfuturestress(mapinlowercenter).Futureclimatestressandsourceinformationforbiodiversitymapdescribedinpriorsectionsofthechapter.2020ResourcesPlanningActAssessment10-25FutureClimateandBiotalandsthereforeoffersthebestpathforbiodiversityconservationandprotectionintheEasternUnitedStates.Thepotentialeffectsoffutureclimateonterrestrialandaquaticbiotaarerelevanttomanagementdecisionsbeingmadetoday.IntheWesternUnitedStates,stressispatchierindistributionWethereforeexaminedhowfutureclimatestresscouldintersectthanintheEastandderivesprimarilyfromdevelopmentterrestrialandaquaticbiodiversitypatternsbyoverlayingtheandclimatechange.Thehigherproportionofthelandinfutureclimatestressmapontoourbiodiversitymaps.FederalownershipintheWestpresentsanopportunityforbiodiversityconservationatbroadspatialscalesTheeasternportionofthecountrycontainstheareasofhighestcommensuratewithclimatestressandwildfire.Whileterrestrialandaquaticbiodiversity.Whenoverlaidwithclimatecollaborationwithpartnersandnon-Federalentitiescanstress,weseesomesimilaroverallpatterns.Forterrestrialbiota,enablethemaintenanceofecologicalprocessesandhabitattheoverlapwithclimatestressshowsareasofhighvulnerabilityconnectivity,theremaybeopportunitiestotrackandintheAppalachianandOzarkMountains,aswellasinthefacilitatemigrationofecosystemsandspeciesintohabitatsMadreanSkyIslands.Additionalareasofbothhighterrestrialmoreconducivetosurvivalasclimateandlandscapesshift.biodiversityandhighclimatestressarefoundinsouthernTexasManagementcouldbenefitfromadditionalconsiderationandintheNortheast(figure10-24).VulnerabilityofaquaticofclimatevulnerabilityplanningthatsupportschangeasbiodiversitytoclimatestressisalsocenteredintheAppalachianecosystemstransitioninresponsetoclimatereality(WestandOzarksMountains(figure10-25).Areasofhighclimateetal.2009),includingresiliencetodisturbancessuchasstressbutlowbiodiversityarefoundthroughouttheWesternwildfire(e.g.,Ageretal.2020).States.Althoughtheseareasmayhaveloweroverallbiodiversity,theysupportimportantecosystems,makingidentificationofConclusionsareasofhighclimatestressimportantformanagementdecisions.ThediversityofanimallifedescribedinthischapterManagementImplicationscontributestoourwell-being,ourlivelihoods,andournationalidentity.OuranalysisdemonstratesthatecosystemsacrosstheTheobservedongoingdeclineinlong-termbiodiversityandcountryarevulnerabletoavarietyoffactorsincludinglandincreasesinESAlistingstatusacrosstaxasignalcontinuedusechange,climatechange,andbiologicalinvasions.Ourbioticandanthropogenicthreatstonativebiodiversityacrossanalysisalsodemonstratesthatthreatsvaryacrossthecountry,theconterminousUnitedStates.Thevulnerabilityofnativewithdifferentcombinationsofthreatsassociatedwithdifferentbiota,particularlytolanduseandprojectedclimatechange,underlyingtopographic,climatic,andsettlementpatterns.highlightstheimportanceofprioritizinghabitatconservationThesecombineddrivershavecontributedtothecurrentactionsinresponsetolocalandregionalthreats.Federalmosaicofintersectinglandusesandnativeecosystemsthatlands,includingnationalforestsandnationalparks,canplaydefinedifferentregionsacrossthecountry.aroleinprovidinglong-termrefugiaaslandscapestransitionintonovelfutureecosystems.Ouranalysisprojectsthatlandusepressures—includinglandconversion,humanpopulationgrowth,expansionofDifferentregionsofthecountryexperiencespecificandagriculturalareas,anddevelopmentofenergyinfrastructureuniquelyinteractingthreats.Forexample,compoundedandmining—willbemostpronouncedintheNorthRegion,aslandusestressorsdominatetheEasternUnitedStates,whilewellasareasoftheSouth,driveninlargepartbypopulationdevelopmentistheprimarylandusestressorofhabitatsgrowth.LandusechangehasbeenidentifiedasathreatintheWest.Climatechangestress,however,isexpectedtospeciespersistence(Smith-HicksandMorrison2021),tobehighestinhigherelevationareas,butalsocreatesaparticularlyinterrestrialsystems(Salaetal.2000),owingtomosaicofhighstressacrossthecountrywhereitinteractsavarietyofimpairmentstohabitatsincludingreductionsinwithdisturbanceprocessessuchaswildfire.Becausethesequantity,quality,andconnectivity(PowersandJetz2019).Forstressorscontributetobiodiversityloss,landmanagersinexample,endemicspeciesthatarespecializedandregionallydifferentregionswillfaceuniquecombinationsofstressors.isolatedareinherentlyvulnerabletoshiftsinlandcoverandhumanpopulationpressureorclimate(Malcolmetal.2006),Non-FederallandsintheRPANorthandSouthRegionsreflectingapotentiallylimitedadaptivecapacitytosurviveareprojectedtobehighlyvulnerabletocompoundedlandasconditionschange.Landusechangescompromiseandusestressinthecomingdecades,increasingtheimportancereducelocalhabitatavailabilityand/orqualityandmayhaveofFederallandstoserveasrefugiaforbiodiversity.Theamoreimmediateeffectonendemicspeciescomparedwithamountoffederallyownedlandintheseregionsislimited,broadlydistributedspeciesforwhichsomeportionofthehowever,andthefactthattheyarethemostbiodiversepopulationmaybeabletofindrefugeonFederalorotherregionsintheconterminousUnitedStateshighlightstheprotectedlands.Highlymigratoryspeciesarealsouniquelydifficultyformanagersseekingtoconserveandprotectvulnerabletoclimatechange,astheirlifestagesarelinkedtobiodiversity.Collaborationacrossbothpublicandprivate10-26FutureofAmerica’sForestsandRangelandsspecifichabitatconditionsatspecifictimes(e.g.,phenology).ObservedpatternsinthelistingstatusofimperiledspeciesDecouplingoftheselinkagesasclimateandlandusechangesundertheESAshowsomeoverlapbetweenareasofhighindifferentwaysindifferentplacesalongtheirmigratorybiodiversityandlocationscontaininglargernumbersofjourneymayincreasetheiroverallvulnerability(Robinsonetlistedspecies.However,ESAlistingbiastowardslarge-al.2009).ThehighconcentrationoflandusestressintheRPAbodiedcharismaticspeciesforwhichlong-termdataoftenNorthandSouthRegionshighlightstheconservationroleofexist,suggeststhatcurrentpatternsofimperiledspecieslimitedFederallandsintheEast,whichalsocoincidewithmaynotnecessarilyreflectspecies-specificthreatsacrosstheareasofhighestterrestrialandaquaticbiodiversityinthethecountry(e.g.,amphibians,Gratwickeetal.2012).InconterminousUnitedStates.recognitionofthechangestotheenvironmentthatarestressingnativebiota,itisimportanttolookforadditionalClimate-drivenstressishighestinthePacificCoastRegionvulnerablepopulationsofbiotathatarenotcurrentlytargetedandpartsoftheRockyMountainRegion—areasthathaveaforconservation.AdditionalFederallistingdecisionsforlargeshareofFederallandsincludingNFS,NPS,andFWSspeciesofconcerncouldoccurasclimateandlanduselands—alongwiththeNorthRegion.OurmodelingindicatescontinuetoaffecthabitatsacrosstheUnitedStates.thatclimatechangemaycompromisetheabilityoffederallymanagedlandstoproviderefugiatonativebiota.ProtectionLiteratureCitedofnativeecosystems(thatwilllikelymorphintonovelonesastheymigrateinresponsetoachangingclimate)willlikelyAbood,S.A.;Maclean,A.L.;Mason,L.A.2012.Modelingriparianrequirecollaborationandcooperationfrompublicandprivatezonesutilizingdamsandfloodheightdata.Photogrammetriclands.Inaddition,managementapproachesthatarebasedonEngineeringandRemoteSensing.78:259–269.pastandcurrentclimatemaybenefitfromupdatestoconsiderdifferentfutureclimatesandthepotentialforgreaternumbersAdams,S.B.2013.Effectsofsmallimpoundmentsondownstreamofdiscreteandcompoundstressevents(e.g.,drought,heat,crayfishassemblages.FreshwaterScience.32:1318–1332.andwildfire)(HagermanandPelai2018,IPCC2021).Ager,A.A.;Barros,A.M.G.;Houtman,R.;Seli,R.;Day,M.A.2020.InadditiontobioticandanthropogenicstressorsvaryingModellingtheeffectofacceleratedforestmanagementonlong-termacrossregions,biotaindifferentpartsofthecountrywillwildfireactivity.EcologicalModelling.421(1):108962.likelyalsoexperiencedifferenttypesofstressesovershortandlongtimescales.Althoughprojectionslooktothefuture,Allan,J.D.2004.Landscapesandriverscapes:theinfluenceoflandthedocumented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0ResourcesPlanningActAssessment11-1OutdoorRecreationResourcesLocal—Thereisnocomprehensiveenumerationoftheextentorlocationofoutdoorrecreationresourcesmanaged❖Forestsandothernaturalresourcesofferbylocalgovernments.Thesepubliclandscanrangefromsmall“pocketparks”thatprovideforshortrespites,toabundantpublicandprivateoutdoorrecreationlargerurbanparkswherepeoplepicnic,walk/hike,orrelax,opportunities.tocountyparksystemsthatofferamyriadofrecreationopportunities.Amongpubliclands,thosemanagedbylocal❖Dataonthenumberandtypesofrecreationgovernmentsaretypicallytheclosesttopopulationcenters.Forthoselivinginorvisitingurbanandperi-urbanareas,resourcesintheUnitedStatesarelimited,thesepubliclandsgenerallyofferthemost-accessiblespacesespeciallyforlocal-government-managedlandsfornature-basedoutdoorrecreation.Localgovernmentandprivatelyownedforestsandrangelands.publiclandstypicallyofferopportunitiestoengageinthemost-popularoutdoorrecreationactivities,suchaswalking/❖FederallandsandWildernessarehiking,viewingnatureandwildlife,andsimplyrelaxingintheoutdoors,andoftenaccommodatethosewithawidedisproportionatelylocatedintheWest,offeringrangeofskillsandabilities.greateracreageunderpublicmanagementforoutdoorrecreation,especiallyindispersedsettings,ThemostextensivedataonoutdoorrecreationopportunitiesundevelopedexperiencesuniquetodesignatedmanagedbylocalgovernmentscomefromTheTrustforWilderness,andnationalparksandassociatedPublicLand’sannualCityParkFacts.ThosedataprovideareasmanagedbytheU.S.NationalParkService.insightintothecharacteristicsofparkandopen-spaceresourcesinthe100most-populatedU.S.cities.In2020,❖Privatelandscanofferuniquerecreationtherewereslightlymorethan2millionacresofparksandopenspaceinthe100most-populatedU.S.cities—manyopportunities,butthoseopportunitiesareoftenofthoseacresmanagedbyStateorFederalgovernmentavailableonlytoownersandtheirfriendsandagencies.In2020,about835,000acresofparksandopenrelativesorthosewhocanpurchaseaccess.spaceinthemostpopulatedU.S.citiesweremanagedbylocalgovernments(TheTrustforPublicLand2020).❖IncreasedfrequencyandseverityofdisturbanceThatlandareahasremainedsteadysince2017.OwingtoachangeinhowCityParkFactsdataarecollected,resultingfromclimatechangemayreduceexaminationoveralongertimeframeisnotpossible.Thetheavailabilityandconditionofrecreationsizeofurbanopenspacesrangeswidely,butmostareopportunities.relativelysmall.Themediansizeofparksandopenspaceinthe100most-populatedcitieswas3.8acres(TheTrustforForests,rivers,rangelands,andothernaturalresourcesPublicLand2020).Seventypercentofthepopulationsintheprovidesettingsconducivetooutdoorrecreation.Justaslargestcitieslivewithina10-minutewalkofanurbanparkcurrentandprojectedforestconditionsdefinethepotential(TheTrustforPublicLand2018).supplyoftimber,wildlifehabitat,andcarbonsequestration,theextentandcharacteristicsofnaturalresources,nowState—AvarietyofagenciesinStategovernmentsmanageandinthefuture,definetheopportunitiesthatpeoplehavelandsandwatersavailabletothepublicforoutdoor(andwillhave)toengageinoutdoorrecreation.Outdoorrecreation.Althoughoutdoorrecreationiscentraltotherecreationpursuitsarediverse,withtheenvironmentsandmissionsofStateparkagencies,otherState-levelagenciesconditionsnecessaryforengaginginoutdoorrecreationthatfocusonforestry,wildlife,landconservation,orotherequallyvariable.Someactivities,suchasfishingandnaturalresourceusesalsooftenprovidepublicrecreationcanoeing,requireaspecifictypeofresource(water)whileopportunities.However,theacresavailableforrecreationotheractivities,suchashikingorviewingnature,cantakeandthetypesofrecreationopportunitiesofferedbythoseplaceinarangeofsettings(e.g.,forests,rangelands,andotheragenciesarenotwelldocumentednationally.Inurbanopenspace).Inadditiontothediversityinresourcegeneral,ourbestunderstandingofrecreationopportunitiesneedsforoutdoorrecreation,outdoorrecreationistsprovidedbyStateagenciescomesfromStateparksandStatethemselvesarediverseintheirdesiresforvarioussettingstoforestryagencies.recreate.WecharacterizerecreationsupplyacrossavarietyoflandownershipsandnaturalresourcetypesinordertoIn2017,StateparksystemsacrosstheUnitedStatesrecognizethisdiversity.managed18.7millionacres(SmithandLeung2019).AmongRPAregions(seefigure2-1forRPAregionPublicLandResourcesdesignations),theNorthRegioncontainsthegreatestStateparkacreage(8.2million),followedbythePacificCoastFromtownparkstoStateparkstonationalforests,publiclandsforrecreationareprovidedateverylevelofgovernment:local,county,State,andFederal.IntheUnitedStates,weoftenlooktopubliclyownedlandsasprimaryprovidersofplacesforoutdoorrecreation.Therecreationopportunitiesofferedbygovernmentsdifferintheirnaturalsettings,locationsrelativetopopulationcenters,andtypes.11-2FutureofAmerica’sForestsandRangelandsRegion(5.3million)(table11-1).AcrosstheentireUnitedremainedsteadyinrecentyears.In2018,StateforestryStates,theareaofStateparksystemshasincreasedsteadilyagenciesspentabout$43milliononrecreationprogramssincethemid-1980s(SmithandLeung2018).Between2009(NationalAssociationofStateForesters2019),withStateand2017,theacreageofStateparkagenciesincreasedbyagenciesintheNorthRegionaccountingformorethanhalfabout33percent(SmithandLeung2019);however,thatofexpendituresinsupportofrecreation.increaseprimarilyreflectsmergersofotherStateagenciesintoStateparksystems,ratherthanmovementoflandsintoFederal—SevenFederalagenciesprovidethemajorityofpublicownershiporchangesinpublicaccess.Thegreatestrecreationopportunitiesonfederallymanagedlands.TheincreasesinStateparkagencyacreagehavetakenplaceindiversityofrecreationopportunitiesprovidedonFederaltheRPARockyMountainRegion(1.4millionacres,102landsparallelsthediversityofthemanagingagencies’percent)andtheRPANorthRegion(3millionacres,57missionsandorigins.Ingeneral,Federallandsaremostpercent).FortheRockyMountainRegion,theincreaseincommonintheWest(Vincentetal.2020)butareprominentacreagetracesprimarilytoanapproximately1-million-acreineveryRPAregion(table11-2).TheU.S.BureauofincreasefollowingthemergerofColoradoStateParksandLandManagement(BLM),withlandsalmostexclusivelyColoradoDivisionofWildlife.IntheNorthRegion,theintheWest,managesthelargestlandareaofanyFederalincreaseinacreageisdrivenbya2.9-million-acreincreaseagency.Althoughthereareimportantexceptions,ingeneralintheStateparksystemofNewYorkState,between2013therecreationresourcesoftheBLMfocusondispersedand2015,thatresultedfromchangesinagencyreporting.recreationinrangelandsettingswithlimitedorlightlyExpendituresforoperatingStateparkagenciesintheUniteddevelopedrecreationfacilitiesandinfrastructure.TheStatestotaled$2.6billionin2017(SmithandLeung2018).U.S.DepartmentofAgriculture(USDA),ForestServiceAlthoughthatisgreaterthanthespendinginthemid-1980sisthenextlargestFederalprovideroflandsforrecreation.(afteradjustingforinflation),theexpendituresinsupportTheUSDAForestServicemanagesarangeofrecreationofStateparkoperationhavebeendecliningyearoveryearresourcesthatsupportawidevarietyofrecreationactivitiessincethemid-2000s(SmithandLeung2018).andsettings.LandsmanagedbytheUSDAForestServicearelocatedacrosstheUnitedStatesbutaremorecommonStateforestryagenciesoftenhaveresponsibilityforintheWest.TheU.S.NationalParkService(NPS)ismanagingrecreationopportunitiesonStateforestsandotherwidelyrecognizedbythepublicasaproviderofkeystoneStatelands.Thereareabout76millionacresofState-ownedrecreationopportunities.Inadditiontonationalparks,theforestsintheUnitedStates,andthisacreagehasremainedNPSmanagesnumerousnationalhistoricsites,nationalsteadytoslightlyincreasinginrecentyears.Althoughtheremonuments,nationalrecreationareas,nationalseashores,areasubstantialnumberofacresmanagedbyStateforestryandotherunits.AlthoughthemajorityofNPSlandsareinagencies,theworkforcededicatedtomanagingrecreationtheWest,agreaterrelativeshareoflandsmanagedbytheislimited.In2018,acrossallStateforestryagencies,fewerNPSareintheEast,comparedtotheUSDAForestServicethan500seasonalpositionswerededicatedtomanagingandBLM.TheNPSprovidesdiverserecreationsettingsrecreation(NationalAssociationofStateForesters2019).andopportunities,includinghighlydevelopedfacilitiesandAgenciesintheRPANorthRegionaccountedforthegreatestinterpretivesites.numbersofseasonalpositionsfocusedonrecreation.ThenumberofseasonalemployeesdedicatedtorecreationhasFourotherFederalagenciesprovidetheremainingFederalrecreationopportunities.TheU.S.FishandWildlifeServiceTable11-1.AcresinStateparksystemsbyRPAregion.YearPacificCoastRockyMountainNorthSouthGrandtotal(acres)20095,176,2281,395,8135,183,8512,217,45313,973,34520105,203,4691,188,0915,366,1192,239,54313,997,22220115,227,8721,298,2985,215,3572,256,92113,998,44820125,250,9541,070,9325,230,0132,370,26313,922,16220135,255,2562,283,5625,242,1082,366,58715,147,51320145,275,1802,456,9723,892,2002,318,86413,943,21620155,262,6992,597,6208,135,7302,376,46118,372,51020165,271,4932,818,6608,117,5022,389,87318,597,52820175,306,2582,822,3948,165,8242,400,09418,694,570Totalregionarea415,728,000538,203,520743,325,440574,086,4002,271,343,360AlthoughsubsequentmodelingandsimulationsexaminetheRPAPacificCoastRegionasdefinedwithintheconterminousUnitedStates,thistablepresentssummariesontheStateparksystemsrelativetotheentirecountry,includingAlaskaandHawaii.Sources:SmithandLeung2019,Vincentetal.2020.2020ResourcesPlanningActAssessment11-3Table11-2.AreaofFederallandandpercentage(relativetocombinedStates’arenearlyexclusivelyintheSouthandWest.Inadditiontotalacreage)byRPAregionandFederallandmanagerin2018.totheland-focusedFederalagencies,theNationalOceanicandAtmosphericAdministration’sOfficeofNationalRPAregionTotalFederalTotalacreageFederalMarineSanctuariesmanagesasystemof15nationalmarineacreage(1000s)inRPAregionacreage(%)sanctuariesand2marinenationalmonumentsthatprovideNorthforshore-andocean-goingrecreationwithintheoceanandBLM15,963(1000s)3.8%GreatLakes.USDAForest5415,728Service4.7%Numerousspeciallydesignatedareas,identifiedthroughFWS12,300538,204Congressionallegislation,andproclaimedareas,establishedNPS35.1%bytheExecutiveBranch,arepresentwithinFederalACOE1,468743,325recreationlands.TheseresourcesincludeWilderness,1,38144.0%nationalwildandscenicrivers,nationalscenicareas,andSouth809204,499nationalmonuments.DesignatedWildernessareasareBLM25,363establishedundertheWildernessActof1964andconstituteUSDAForesttheNationalWildernessPreservationSystem(NWPS).Service29WildernessareasaredesignatedtopreservelandswithoutFWShumandevelopmentandwithnaturalprocessesastheNPS13,391centerpiece.InWilderness,recreationislimitedtonon-ACOEmechanizedopportunitiesandoccursindispersedsettings.3,424WildernessisgenerallythoughttosupplysomeoftheRockyMountain5,122bestopportunitiesforsolitudeandremoteness.AlthoughBLM3,397Wildernessareastendtobefarfrompopulationcenters,USDAForest260,558manyarereadilyaccessibletopopulatedplaces.TheNWPSService141,692extendsacross44Stateswithover109millionacresthatareFWSmanagedbyfourFederalrecreationagencies(Carlsonetal.NPS99,2652016)(table11-3).TheNPSmanagesthegreatestnumberACOEofNWPSacres(44million),accountingformorethanhalf6,319oftheNPSlandbase(Hoover2014).TheUSDAForestPacificCoast10,985Servicemanagesthesecond-greatestnumberofNWPSacresBLM2,297(36million),butthoselandsamounttolessthanone-fifthofUSDAForest89,930USDAForestService-managedlands.Nearly95percentofService31,268theWildernessacresmanagedaspartoftheUSDAForestFWSServiceNationalForestSystem(NFS)areintheWest,withNPS45,824nearlyequalamountslocatedintheRPARockyMountainACOEandPacificCoastRegions(18and16millionacres,1,036respectively).TheRPASouthRegionhaslessthan1million9,644acresofWilderness,whiletheNorthRegionhasabout1.52,158millionacres.Thisdistributionreflects,inpart,thepresenceoflandthatmettherequirementsfordesignationundertheACOE=U.S.ArmyCorpsofEngineers;BLM=U.S.BureauofLandManagement;FWS=U.S.FishWildernessAct.ThespatialdistributionofNFSWildernessandWildlifeService;NPS=U.S.NationalParkService.meansthatthoselivingintheWesthavemarkedlygreaterU.S.BureauofReclamationfacilitiesarenotpresentedhere.accesstoWildernesscomparedtothoselivingelsewhere.PacificCoastRegiondoesnotincludeAlaskaorHawaii.Source:Vincentetal.2020.(FWS)providesavarietyofrecreationopportunities,althoughwithprimaryrecreationfocusonwildlife-relatedrecreation.TheU.S.ArmyCorpsofEngineers(ACOE)andU.S.BureauofReclamation(BOR)primarilyproviderecreationopportunitiescenteredonwaterwaysandflood-andirrigation-controlfacilities.TheACOEhasfacilitieslocatedacrosstheUnitedStates,whiletheBORfacilitiesTable11-3.Acres(1,000s)intheNationalWildernessPreservationSystembyFederalagencyandRPAregion,circa2012.RPAregionUSDAForestServiceNPSFWSBLMRegiontotalNorth1,4321796401,675South7541,48747002,711RockyMountain18,1881,34925,614PacificCoast15,77740,8851,4654,61179,455Federalagencytotal36,15143,90018,7044,089109,45520,7038,701PacificCoastRegiondoesnotincludeAlaskaorHawaii.Source:Hoover2014.11-4FutureofAmerica’sForestsandRangelandsRPAScenariosTheRPAAssessmentusesasetofscenariosofcoordinatedFigure11-1.Characterizationofthe2020RPAAssessmentfutureclimate,population,andsocioeconomicchangetoscenariosintermsoffuturechangesinatmosphericwarmingandprojectresourceavailabilityandconditionoverthenext50U.S.socioeconomicgrowth.Thesecharacteristicsareassociatedyears.ThesescenariosprovideaframeworkforobjectivelywiththefourunderlyingRepresentativeConcentrationPathwayevaluatingaplausiblerangeoffutureresourceoutcomes.(RCP)–SharedSocioeconomicPathway(SSP)combinations.The2020RPAAssessmentdrawsfromtheglobalSource:Langneretal.2020.scenariosdevelopedbytheIntergovernmentalPanelonClimateChangetoexaminethe2020to2070timeperiod(IPCC2014).TheRPAscenariospairtwoalternativeclimatefutures(RepresentativeConcentrationPathwaysorRCPs)withfouralternativesocioeconomicfutures(SharedSocioeconomicPathwaysorSSPs)inthefollowingcombinations:RCP4.5andSSP1(lowerwarming-moderateU.S.growth,LM),RCP8.5andSSP3(highwarming-lowU.S.growth,HL),RCP8.5andSSP2(highwarming-moderateU.S.growth,HM),andRCP8.5andSSP5(highwarming-highU.S.growth,HH)(figure11-1).Thefour2020RPAAssessmentscenariosencompasstheprojectedrangeofclimatechangefromtheRCPsandprojectedquantitativeandqualitativerangeofsocioeconomicchangefromtheSSPs,resultinginfourdistinctfuturesthatvaryacrossamultitudeofcharacteristics(figure11-2),andprovidingaunifyingframeworkthatorganizestheRPAAssessmentnaturalFigure11-2.Characteristicsdifferentiatingthe2020RPAAssessmentscenarios.ThesecharacteristicsareassociatedwiththefourunderlyingRepresentativeConcentrationPathway(RCP)–SharedSocioeconomicPathway(SSP)combinations.2020ResourcesPlanningActAssessment11-5resourcesectoranalysesaroundaconsistentsetofpossibletodevelopclimateprojectionsforbothlowerandhigh-worldviews.TheScenariosChapterdescribeshowthesewarmingfutures,therearedistinctclimateprojectionsforscenarioswereselectedandpaired;moredetailsareeachmodelassociatedwithRCP4.5andRCP8.5.TheprovidedinLangneretal.(2020).ScenariosChapterdescribeshowtheseclimatemodelswereselected.JoyceandCoulson(2020)giveamoreThe2020RPAAssessmentpairsthesefourRPAscenariosextensiveexplanation.withfivedifferentclimatemodelsthatcapturethewiderangeofprojectedfuturetemperatureandprecipitationThroughouttheRPAAssessment,individualscenario-acrosstheconterminousUnitedStates.AnensembleclimatefuturesarereferredtobypairingRPAscenariosclimateprojectionthataveragesacrossthemultiplewithselectedclimateprojections.Forexample,anmodelprojectionsisnotusedbecauseoftheimportanceanalysisrununder“HL-wet”assumesafuturewithofpreservingindividualmodelvariabilityforresourcehighatmosphericwarmingandlowU.S.populationandmodelingefforts.ThefiveclimatemodelsselectedbyRPAeconomicgrowth(HLRPAscenario),aswellasawetterrepresentleastwarm,hot,dry,wet,andmiddle-of-the-climatefortheconterminousUnitedStates(wetclimateroadclimatefuturesfortheconterminousUnitedStatesprojection).(table11-4);however,characteristicscanvaryatfinerspatialscales.AlthoughthesamemodelswereselectedTable11-4.Fiveclimatemodelsselectedtoreflecttherangeofthefullsetof20climatemodelsintheyear2070.EachmodelwasrununderRCP4.5andRCP8.5,providingarangeofdifferentU.S.climateprojections.ClimatemodelLeastwarmHotDryWetMiddleInstitutionIPSL-CM5A-MRNorESM1-MMRI-CGCM3HadGEM2-ESCNRM-CM5InstitutPierreSimonNorwegianClimateMeteorologicalMetOfficeHadleyLaplace,FranceNationalCentreCenter,NorwayResearchInstitute,Centre,UnitedofMeteorologicalKingdomResearch,FranceJapanSource:JoyceandCoulson2020.RCP=RepresentativeConcentrationPathway.PrivateLandResourcesfamilies(Butleretal.2020).Althoughrecreationwasoftenviewedasanimportantreasonforowningland,onlyasmallTheapproximately459millionacresofforestsownedshareofthatforestlandismanagedtoimproverecreationbyindividualsandfamilies,privatebusinesses,andlandopportunity.Approximately25percentofindividualandtrustsandcommunity-ownedforestsproviderecreationfamilyforestlandacres(and14percentofownerships)opportunitiesformanyintheUnitedStates.However,dataarepartofholdingsthathavehadtrailimprovements,andarelimitedontheuseofsomeoftheselandsforrecreationabout35percentofacres(13percentofownerships)arepartandtheiravailabilitytothepublicforrecreation.Recreationofholdingsthathaveundergonemanagementtoimproveopportunityonforestsownedbyindividualsandfamilieswildlifehabitatinthelast5years(Butleretal.2020).(272millionacresacrossthecountry)isalmostexclusivelyavailableonlytotheowners’familiesandfriends(ButleretAnothersourceofrecreationopportunityisthemanyal.2020).Approximately56percentofthelandownedbyforestindustrycorporationsthatmaketheirlandsatleasttheseindividualshasbeenusedinrecentyearsforrecreationpartiallyavailabletothepublic.Manylargecorporateforestbytheowners,while46percenthasbeenusedbythelandowners(i.e.,thoseowningmorethan45,000acres)owners’childrenand41percentbyowners’friends(Butlerprovideamixoffreeandfee-basedrecreationopportunities.etal.2020).IndividualandfamilyforestparcelsgreaterthanInasurveyoftheseowners,74percentreportedallowing10acresinsizearemorelikelytobeusedforrecreationpublicrecreationaccessforfreeand85percentforafeebyowners,family/friends,orthepublic(Butleretal.2016,(Sass,personalcommunication).Ingeneral,recreationisaButlerandSnyder2017).Ownersidentifyrecreationasalow-prioritymanagementobjectiveofcorporatelandowners“veryimportant”or“important”reasonforowningabout(Sassetal.2021).Somewherebetween15and75percenthalfoftheforestlandacresownedbyindividualsandofcorporateowners(dependingoncompanytype)reported11-6FutureofAmerica’sForestsandRangelandshuntingasanownershipobjective,whilelessthan40opportunitieswhennewlandownersrestrictaccessthatwaspercentreportedrecreation(moregenerallyspeaking)aspreviouslygranted.anownershipobjective(notmutuallyexclusivecategories)(Sassetal.2021).Howprojectedlandusechangemayaltertheavailabilityofnon-federallyownedforestsforrecreationcanbeexploredbyLocal,State,andnationallandtrustsandcommunityforestsexaminingthejointprojectionsoffuturelanduse(describedproviderecreationopportunitiesonmanylandstheymanage.intheLandResourcesChapter)andpopulation(describedIn2015,landtrustswereresponsibleforconservationintheScenariosChapter)underthe2020RPAAssessmenteffortsonabout56millionopenspaceacresacrossthescenarios(seethesidebarRPAScenarios).LookingtowardUnitedStatesandownedabout8millionofthoseacres2040(andusingthemiddleclimateprojectionforillustrationof(LandTrustAlliance2016).Morethan70percentoflandspotentialscenariodifferences),manyareasoftheUnitedStatesmanagedbylandtrustsnationallyareopenforrecreation.areprojectedtoexperiencemodestchangeinpercapitanon-Likemanylandowners,landtrustsoftenspecifywhichfederalforestarea(figure11-3).Underthemoderatepopulationrecreationactivitiesarepermittedonlandstheymanage.andeconomicgrowthRPAscenario(LM),slightormoderateForexample,recreationactivitiesmaybelimitedtothosedeclinesinforestareaaremosttypicalfor2040.Incontrast,ifthatarenon-consumptiveandnon-mechanized.Communitypopulationandeconomicgrowthislower(theHLscenario),forests—oftenownedbyanonprofitorganizationorlocalpercapitanon-Federalforestareadeclinesareprojectedtobegovernment—wheremanagementgoalsareguidedbylessandinsomecasesforestareamayincrease.Whengainscommunityboards,arealsooftenopentorecreation.Likeinpercapitanon-Federalforestareaareprojected,theyarelandtrusts,communityforestscanhaverestrictionsonmostcommonlyinnorthernareasoftheRPANorthandRockythetypesofrecreationactivitiesallowedonthelandstheyMountainRegions.Gainsinpercapitanon-Federalforestareamanage.Theareamanagedascommunityforestsacrossthebecomelesscommonundermoderategrowth(LM)andalmostUnitedStatesisunknown(inpartbecausewhatconstitutesanonexistentunderahigh-growthscenario(HH)aslandusecommunityforestispoorlydefinedintheUnitedStates)butconversionratesincrease.Inthelow-growthscenario,projectedislessthantheareamanagedbylandtrusts.lossesinpercapitanon-FederalforestareaaremostlyconfinedtotheRPASouthandsouthernRockyMountainRegions.UnderChangesInfluencingRecreationthegreatergrowthintheLMandHHscenarios,projectedlossesResourcesinpercapitanon-FederalforestareaarefoundineveryregionandaremostsignificantinthefarnorthoftheNorthRegion,LandUseandOwnershipChange—ChangesinlandthenorthernportionsofthePacificCoastRegion,andtheuseandlandownershipcanaltertheavailabilityofbothsouthernportionsoftheRockyMountainRegion.Weusetheprivateandpubliclandrecreationresources.Conversionloweratmosphericwarming(LM)andthehigheratmosphericofprivatelandfromopenspacetodevelopeduses,suchwarming(HL,HH)scenariosheretoexploretherangeofashousing,businesses,orinfrastructure,canreducepotentialforestlandusechangesunderthemiddleclimaterecreationopportunitiesthatwerehistoricallyavailable.projectionanddifferentatmosphericwarminglevels.However,Thisconversioncanresultinareductioninthetotaltheseresultscanalsodifferwithdifferentclimateprojectionsareaavailableforrecreationandincreasedpressureon(seetheLandResourcesChapterfordiscussionofhowaclimatepubliclandrecreationresources,assumingtherecreationmodelinfluenceslanduseprojections).engagementthathistoricallyhappenedonprivatelandisdisplacedtopublicland—forexample,anannualhuntingLookingto2070,theprojectedchangesinpercapitanon-triptoprivatelyownedlandthatnowoccursonStateland.federalforestareaaresimilarinpatterntothosefoundinAlthoughconversiontodevelopedlandusesislesscommonthe2040projections(figure11-4).Modestchangesinperonpubliclyownedlands,changesinmanagementorlandcapitanon-FederalforestareaarestillprojectedformultipledesignationcanaltertheavailabilityofpubliclyownedlocationsineachRPAregion.Whenchangesareprojected,landforrecreation.Suchchangescanbothincrease(e.g.,theyareofgreatermagnitudein2070thanin2040.Fordesignationoflandswhererecreationopportunityistheexample,gainsinpercapitaforestareaintheHLscenarioprimaryfocus)orrestrict(e.g.,expandingareadesignatedandlossesinpercapitaforestareaintheHHscenariomoreforresourceextractionorimplementingacaponthenumberfrequentlyapproach5percent.ofvisitors)recreationopportunity.ClimateChange—ClimatechangecanalternaturalresourceBeyondlandusechanges,changesinpropertyownershipandenvironmentalconditionsinwaysthatchangetheircanalsoalteraccesstorecreationopportunities.Insomedesirabilityforrecreation.Changingclimateconditionscancases,suchasalandtrustpurchasingaproperty,recreationaffectthefrequencyofnaturaldisturbances(e.g.,wildfireaccessmayincreasebecauseofanownershipchange.Inandflooding)withpotentialfordramatic,rapidchangesinothercases,changesinownershipcanreducerecreationresourceconditions,necessitatingsuchmanagerialactionsaslimitingaccesstorecreationresources.Changesinresourceand2020ResourcesPlanningActAssessment11-7Figure11-3.Differencesinnon-Federalforestacrespercapita,2012to2040.Differencesarecomputedastheratioofacres(hundreds)topopulation(tens),forRPAscenarios(a)LowMedium(LM),(b)HighLow(HL),and(c)HighHigh(HH)underthemiddleclimateprojection.Blue/purpleareashaveincreasingpercapitanon-Federalforestlands,whileredareashavedecreasingpercapitanon-Federalforestlands.Areasshadedingray(N/A)havenonon-Federalforestlandsorlackprojectionsduetoinsufficientlandusetransitiondata.abcDifferenceinscaledpercapitanon-Federalforestlands,2040-2012.Figure11-4.Differencesinnon-Federalforestacrespercapita,2012to2070.Differencesarecomputedastheratioofacres(hundreds)topopulation(tens),forRPAscenarios(a)LowMedium(LM),(b)HighLow(HL),and(c)HighHigh(HH)underthemiddleclimateprojection.Blue/purpleareashaveincreasingpercapitanon-Federalforestlands,whileredareashavedecreasingpercapitanon-Federalforestlands.Areasshadedingray(N/A)havenonon-Federalforestlandsorlackprojectionsduetoinsufficientlandusetransitiondata.abcDifferenceinscaledpercapita11-8FutureofAmerica’sForestsandRangelandsnon-Federalforestlands,2070-2012.environmentalconditionscanincludethosethatmakerecreatingEngagementinOutdoormoreorlesspleasant(e.g.,temperaturesthataretoohotornotRecreationascoldastypical)orthatchangethefeasibilityordesirabilityofrecreation(e.g.,lowwaterlevels,changesinnumbersortiming❖Participationrateshavebeensteadyinrecentofflowers,shiftsinbirdmigrationpatterns).Althoughmanyoutcomesfromclimatechangewilllikelyreducerecreationyearswithabout50percentofthepopulationopportunities(e.g.,lossofnaturalsnowinareaspopularforengaginginoutdoorrecreation.snowmobilingorskiing),climatechangemayincreasetheavailabilityofsomerecreationresources.Forexample,lesssnow❖Therelativepopularitiesofindividualnature-andwarmerspringsmayincreasethelengthoftimethatsomewarm-weatherrecreationresourcesaresnow-freeandaccessible.basedoutdoorrecreationactivitieshavebeenInthiscase,climatechangehasmadesnow-basedactivitieslessgenerallystableoverthelastdecadeorlongeropportunewhilepotentiallyfavoringdayhikingorhorsebackwithhiking,fishing,andcampingbeingthemost-ridingontrails.popularactivities.Naturaldisturbances,suchaswildfires,floods,andwindevents,❖Outdoorrecreationparticipationratesamongareecologicalprocessesthathaveshapedthenaturalresourcesweseetoday.Present-daynaturaldisturbanceeventscanminoritygroupsandwomenhavebeeninfluencetheavailabilityofrecreationresourcesbychangingincreasing,albeitslowly.resourceconditionsorbycreatinghazardousconditionsthatresultinmanagersorlandownersreducingorrestrictingaccess❖Publiclandsvisitationhasbeenincreasingtorecreationresources.High-severitydisturbances(e.g.,severewildfire)candramaticallyaltervegetationconditionsverymodestlyattheFederallevelandmorerapidlyatrapidly.Ingeneral,theresearchconductedonsiteinpost-firetheStatelevel.landscapeshasfoundthatrecreationlevelsdropmodestlyimmediatelypost-firebuttrendbacktopre-firelevelsin❖Forthosewhohaveaccess,privatelandsarerelativelyshortorder(e.g.,Brownetal.2008,McCaffreyetal.2013,Whiteetal.2020).Onsitestudieshavefoundindicationsimportantprovidersofrecreationopportunityforthatburnedlandscapesdonotdramaticallychangevisitorhunting,dayhiking,fishing,andmotorizedoff-satisfactionorreduceopportunities(e.g.,Whiteetal.2020),butroaduse.theydoinfluencedecisionsaboutspecifictrailandcampsiteuse(e.g.,LoveandWatson1992,SchroederandSchneider2010).ParticipationinOutdoorRecreationOtherstudieshaveexaminedhowrecreationistsstatetheywouldrespondtohypotheticalburnedlandscapes,generallyAbouthalfoftheU.S.populationage6andolderfindingthatburnedlandscapesreducethevalueofrecreationparticipatesinsometypeofoutdoorrecreation(Outdoorforrecreationistsandthatpost-firelandscapescanhavedifferentFoundation2019).Thatlevelofengagementinrecreationeffectsonrecreationdependingonfireseverityandrecreationhasheldrelativelysteadysince2007(OutdoorFoundationactivity(Bawa2017).Lessisknownabouttheeffectsofhigh-2018).In2018,camping/backpacking,fishing,anddayseverityfloodingeventsonrecreation-resourcedesirability.Overhikingwerethenature-basedoutdoorrecreationactivitiesthelastdecade,publicandprivatelandownershaveenactedwiththegreatestnumbersofparticipants(OutdoortemporaryclosuresoftheirlandstorecreationuseinresponseFoundation2019),withabout13to16percentofthetoactivewildfire,weatherandforestconditionsthatyieldahighpopulationparticipatingineachofthoseactivities.Beyondriskofwildfire,andpost-disturbanceconditions(e.g.,unstablethosethreeactivities,participationratesfornature-basedslopesordeadtrees)thatmaythreatenvisitorsafety.Inaddition,outdoorrecreationactivitiesrangebetweenabout1to10thereisnowpreliminaryevidencethatexistingorpotentialpercentofthepopulation(OutdoorFoundation2019).Thesmokefromwildfireisbeginningtoinfluencewhereandwhenmotivationsmostcitedforengaginginrecreationwerevisitorstakeoutdoorrecreationtrips(e.g.,Gellmanetal.2021,improvementofhealth,spendingtimewithfamilyandWhiteetal.2020).Continuedincreasesinthefrequencyoffriends,experiencingnature,andgettingawayfromothernaturaldisturbancesoverthecomingdecadesmayleadtomoredemands(OutdoorFoundation2018).periodswhennaturalresourcesareunavailableforrecreationuse.ThishasthepotentialtocompressoutdoorrecreationtoOutdoorrecreationparticipantsaredisproportionatelyshorterperiodsduringtheyear,tochangethelocationswheremalerelativetotheU.S.population,althoughparticipationpeoplerecreate,andtoreducethenumberofpeopleengaginginratesamongwomenhavebeenincreasinginrecentyearsoutdoorrecreation.(OutdoorFoundation2019).Peopleunder24typicallyhavethehighestratesofparticipationinoutdoorrecreation,butthoseover25accountformostrecreationparticipants(OutdoorFoundation2018).Themajority(74percent)ofoutdoorrecreationparticipantsareWhiteandaboutathirdhaveannualhouseholdincomesover$100,000(OutdoorFoundation2019)—bothdisproportionatelyhighrelativetotheU.S.population.Withintheirrespectiveethnicities,Asianshavethehighestratesofparticipationin2020ResourcesPlanningActAssessment11-9Table11-5.Most-popularoutdoorrecreationactivitiesbyracialandethnicgroup,2018.WhiteBlackHispanicAsianPercentPercentRankActivityPercentActivityActivityPercentActivityparticipatingparticipatingparticipatingparticipating1Running17.3Running26.12Hiking20.0Biking10.4Running20.6Hiking21.23Fishing9.9Biking16.44Fishing18.2Camping5.9Biking14.7Camping11.35Hiking5.5Fishing9.9Running16.9Hiking14.6Camping16.3Camping14.2Biking15.5Fishing13.2Source:AdaptedfromOutdoorFoundation2019.outdoorrecreation(nearly70percentengaginginoutdoorFreshwaterfishingsawthelargestdeclineinnumberofrecreation),followedbyWhites(nearly53percent)andparticipantsduringtheperiod:alossofabout5million.TheHispanics(morethan40percent).ParticipationamongAsianotherlargestdeclinesinparticipantnumberswereassociatedandPacificIslandersandHispanicshasbeenincreasingwithwildlifeviewing(2million)andbirdwatchingawaysincethe2010s(OutdoorFoundation2019).Participationfromhome(1million).byBlacksinoutdoorrecreationislessthan40percentandgenerallyunchangedfromobservationsintheearly2010s.TheaveragenumberofoutingsbythoseengaginginoutdoorAcrossallracial/ethnicgroups,therewasconsistencyinrecreationhasbeendecliningyearoveryearoverthelastthesetofmost-popularoutdoorrecreationactivities,butdecadeormore(OutdoorFoundation2019).Between2017thepopularityrankingsofspecificactivitieswithinthesetand2018,theaveragenumberofoutingsannuallyperdifferedacrossgroups(table11-5).participantdeclinedby7.4—a10-percentdecline(OutdoorFoundation2018,2019).However,thoseaveragesareFormostnature-basedoutdoorrecreationactivities,theshareofthepopulationparticipatingwasstablebetween2007andTable11-6.PercentofU.S.populationage6andolderengaginginoutdoor2018(OutdoorFoundation2018,2019)(table11-6).Withrecreationactivities,2007,2010,2015,2018.someexceptions,theshareofthepopulationparticipatinginaspecificactivityin2018waswithin1to2percentageActivity2007201020152018pointsofwhatwasobservedin2007.TheshareoftheHiking(day)populationparticipatingindayhikingdidincreasebyaboutCamping(car,backyard,10.811.512.715.95percentagepointsoverthetimeframe,andtheshareofthebackpacking,&RV)populationthatengagedinfreshwaterfishingdecreasedby3Fishing(freshwater/other)15.114.913.613.9percentagepoints.Camping(drivenbylossesincarcampingWildlifeviewingaandcampingoutsideahome)andwildlifeviewingbothHunting(rifle/shotgun/15.813.712.813experienceddeclinesinsharesofthepopulationparticipatinghandgun/bow)thatapproached2percentagepoints.TrailrunningandBirdwatchinga8.37.476.8recreationalkayakingbothsawgainsinparticipationof1Kayaking(recreational)to2percentagepoints,althoughlessthan4percentoftheBackpackinga5.14.95.35.2populationparticipatedinthoseactivities.Skiing(Alpine/downhill)bTrailrunning4.94.74.54.1AlthoughtheshareofthepopulationthatengagedinoutdoorCanoeingrecreationremainedrelativelystableataround50percentBicycling(mountain/non-1.82.33.23.7between2008and2018,thenumberofparticipantsinpavedsurface)outdoorrecreationincreasedbyabout15millionindividualsSnowboarding2.42.93.43.5becauseofcontinuedU.S.populationgrowth(OutdoorSkiing(cross-country)Foundation2019).TheincreasingnumberofoverallSailing3.73.83.2outdoorrecreationparticipantswasmirroredbygrowthinSnowshoeingthenumberofparticipantsengaginginmanyindividualRafting1.51.82.83.3outdoorrecreationactivities.ForthoseactivitiesgainingKayaking(sea/touring)participants,increasestypicallyrangedbetweenabout1Kayaking(whitewater)3.53.73.53and4millionnewparticipants(table11-7).However,dayClimbing(traditional/ice/hikingexperiencedagainofabout18millionadditionalmountaineering)2.52.52.82.9participantsbetween2007and2018.Recreationalkayakingandtrailrunningeachexperiencedabout6millionnew2.52.62.62.4participantsoverthatperiod(OutdoorFoundation2019).1.31.51.41.71.41.41.41.20.91.21.31.21.61.61.31.10.50.810.90.40.60.90.90.80.80.90.8aMorethan1/4milefromvehicle/home.bNodataavailablefor2018duetoredefinitionofskiingaggregatefromAlpine/DownhilltoAlpine/Downhill/Freeski/Telemark(OutdoorFoundation2019).Source:OutdoorFoundation2019.11-10FutureofAmerica’sForestsandRangelandsTable11-7.Numberofindividualsage6andolderengaginginoutdoorDespitetheirgreaterparticipationrelativetoadults,youthrecreationactivities(millions),2007,2010,2015,2018.participationratesinoutdoorrecreationhavedeclinedslightlyinrecentyears(OutdoorFoundation2019).AmongActivity2007201020152018nature-basedoutdoorrecreationactivities,youthwereHiking(day)mostlikelytoparticipateincamping,fishing,anddayCamping(car,backyard,3032.537.247.9hiking(table11-8).Youthhadhigherratesofparticipationbackpacking,&RV)thanadultsforallactivitiesexceptwildlifeviewingandFishing(freshwater/other)41.742.34041.7birdwatching,snowshoeing,andtrailrunning.ParticipationWildlifeviewingaratesbyyouthinspecificoutdoorrecreationactivitieshaveHunting(rifle/shotgun/43.938.937.739beenrelativelystableoverthelastdecadeormore.However,handgun/bow)thereweremarginalincreasesinparticipationratesforBirdwatchinga232120.720.6dayhiking,kayaking,andhunting,andsmalldeclinesforKayaking(recreational)campingandfishing.Backpackinga14.11415.515.7Skiing(Alpine/downhill)bInadditiontohavinggreaterparticipationinoutdoorTrailrunning13.513.313.112.3recreationthanadults,youthalsohadmorefrequentCanoeingengagementinrecreation.YouthparticipantsinoutdoorBicycling(mountain/non-5.16.59.511recreationaveragedmorethan76outingsayearinpavedsurface)recreationalpursuits.Onaverage,youthengagedinrunningSnowboarding6.68.310.110.5(includingtrailrunning)andbikingnearlyweekly(45andSkiing(cross-country)40outingsperyear,respectively).Outingsfornature-basedSailing10.410.99.4outdoorrecreationoccurredlessoften,withbetween15andSnowshoeing16outingsayearfordayhikingandfishing,respectively,Rafting4.25.18.110and11outingsayearforcamping.Kayaking(sea/touring)Kayaking(whitewater)9.810.610.29.1Climbing(traditional/ice/mountaineering)6.97.28.38.76.87.47.77.13.54.24.15.13.83.94.13.82.43.43.93.54.34.53.93.41.52.13.12.81.21.82.52.62.12.22.62.5Table11-8.PercentofU.S.populationages6to18engaginginoutdoorrecreationactivities,2007,2010,2015,2018.aMorethan1/4milefromvehicle/home.bNodataavailablefor2018duetoredefinitionofskiingaggregatefromAlpine/DownhilltoAlpine/Activity2007201020152018Downhill/Freeski/Telemark(OutdoorFoundation2019).Source:OutdoorFoundation2019.Camping(car,backyard,24.32321.120.5backpacking,&RV)Fishing(freshwater/other)21.717.818.617.5driven,since2014,byareductioninengagementbytheHiking(day)11.511.91516.1participantswhorecreateveryfrequently.In2014,thoseparticipatinginmorethan100outdoorrecreationoutingsWildlifeviewinga5.966.47.1peryear—themostavidrecreationists—accountedforabout22.3percentofallannualoutings.By2017,thatmost-avidHunting(rifle/shotgun/4.24.46.76groupaccountedforabout20.7percentofalloutings.Overhandgun/bow)thatsameperiod,thoserecreating12to51timesperyearaccountedforanearlyconstantshareofoutingsandtheSnowboarding4.85.146shareofoutingsfromthoseengaginglessthanmonthlyincreasedslightly(OutdoorFoundation2019).Ultimately,Kayaking(recreational)2.12.344.9theshareofoutdoorrecreationistswiththegreatestaviditylevelshasdeclined.In2018,forthosenature-basedTrailrunning1.31.33.14.7outdoorrecreationactivitiesforwhichvaluesarereported,participantsreportedanaverageof18outingsperyearforBackpackinga3.64.45.84.6fishing,14fordayhiking,and13forcamping(OutdoorFoundation2019)(seethesidebarHowCOVID-19InfectionBicycling(mountain/non-3.53.83.83.8RatesandLocationCharacteristicsHaveImpactedUSDAForestServiceCampgroundReservations).pavedsurface)Youthbetweentheagesof6and17hadgreaterratesCanoeing5.15.64.83.8ofparticipationinoutdoorrecreationthantheiradultcounterparts(OutdoorFoundation2018,2019).ThepatternSkiing(Alpine/downhill)b4.44.84.2ofgreateryouthparticipationrates,relativetoadults,hasheldsincethemid-2000s(OutdoorFoundation2018).Birdwatchinga2.43.23.12.9Skiing(cross-country)1.11.52.12.7Kayaking(sea/touring)0.50.71.71.6Kayaking(whitewater)0.40.51.61.6Sailing11.21.81.6Snowshoeing0.81.21.41.4Climbing(traditional/ice/10.71.51.3mountaineering)Rafting21.92.11.2aMorethan1/4milefromvehicle/home.bNodataavailablefor2018duetoredefinitionofskiingaggregatefromAlpine/DownhilltoAlpine/Downhill/Freeski/Telemark(OutdoorFoundation2019).Source:OutdoorFoundation2019.2020ResourcesPlanningActAssessment11-11HowCOVID-19InfectionRatesandLocationCharacteristicsHaveImpactedUSDAForestServiceCampgroundReservationsDuringtheCOVID-19pandemic,U.S.publiclandrisk.Duringthesummerof2020,campgroundsmanagerswerefacedwiththeuniquechallengeofsawanearly40-percentincreaseinaveragenightlymaintainingsocialdistancingrequirementswhilereservations.Themeanweeklynightsreservedperexperiencingincreasedvisitation.Shartajetal.(2022)campgroundstoodat50.35duringtheyear.Thisanalysisinvestigatedthesizeableincreaseinreservationsthatrevealedapositivecorrelationbetweenthenumberofoccurredduringthesummerof2020byanalyzingreservationsatacampgroundandCOVIDinfectionfinalreservationstoNationalForestSystem(NFS)ratesinthesurroundingcounty.PublicpolicieswerecampgroundsintheconterminousUnitedStates(figure11-alsoshowntoaffectcampgroundreservations:stay-at-5).Theauthorshighlightthelocalinfectionrates,publichomeadvisoryorderssignificantlyreducedcampgroundpolicies,andproximitytonationalparks,metropolitanreservationsinboththespringandthesummerof2020.areas,andwildfireonNFScampingdemand.ThestudyshowedthatbeingnearanationalparkorametropolitanareaalsoresultedinconsiderableincreasesCampinghastypicallybeenperceivedasasaferformofinsummertimeNFScampgroundnightsreserved.Theleisureactivityduringperiodsofhighvirustransmissionmagnitudeoftheincreasesduetoproximitytonationalparksandmetropolitanareasrepresent13and27ofFigure11-5.Changesinweeklynightsreservedpercampgroundmeancampingnightsreservedin2020,respectively.between2019and2020byweekforUSDAForestServiceregions.USDAForestServicecampgroundsnearnationalparkssawparticularlylargeincreaseswhenindividualsChangeinweeklyreservationsvisitingnationalparksforotherrecreationactivitiespercampgroundbetween2019and2020campedatNFScampgroundsdueeithertopreferenceorbecauseofnationalparkcampgroundunavailability.NFScampgroundslocatednearpopulatedmetropolitanareasfacedincreasedvisitationduetotravelrestrictionsandgenerallackofCOVID-saferecreationactivities.Finally,campgroundslocatednearwildfireboundariesexperienceddeclinesinnightsreservedintheweeksthatthefireswereactive.MonthMostafaShartaj,ColoradoStateUniversityJordanF.Suter,ColoradoStateUniversityEasternNorthernPacificSouthwestSouthernTravisWarziniack,USDAForestService,RockyMountainIntermountainPacificNorthwestRockyMountainSouthwesternResearchStationSeehttps://www.fs.usda.gov/about-agency/contact-us/regional-officesforregionlocations.TheWorldHealthOrganization(WHO)characterizedCOVID-19asapandemiconMarch11,2020.UseofRecreationResourcesthemost-visitedunitswithinthelocalparksystemsofthe100most-populatedcities(TheTrustforPublicLand2020).LocalandStateGovernments—LocalgovernmentpublicUltimately,manylocalgovernmentssimplylackthefunding,landsprovidereadyaccessforthoselivingincities,towns,capacity,andtoolstoquantifyrecreationuseattheirparksandandresidentialareas.Althoughtheamountofrecreationopenspaces(seethesidebarUsingCrowd-SourcedandSocialuseattheseplacesinaggregateislikelysubstantialbecauseMediaDatatoUnderstandRecreationUse).ofthesheernumberofresourcesandproximitytopotentialusers,thereisnoreliableestimateoftotalrecreationuseatVisitationtoStateparksystemsintheUnitedStateshaslandsmanagedbylocalgovernments.Despitesomelocalincreasedinrecentyearsafteraslowdowninthemid-2000s.governmentsmonitoringtheamountofrecreationuse,thereisIn2018,visitationtoStateparkagencies(813millionvisits)nocomprehensivesystemtocompilethoseestimates.Partialwasgreaterthananyyearsinceconsistentnational-levelaccountingbyTheTrustforPublicLand’sCityParkFactsaccountingbegan(Smithetal.2020).Stateparksystemsinindicatestherearemorethan240millionvisitseachyeartotheRPANorthRegionaccountfornearlyhalfofallvisits11-12FutureofAmerica’sForestsandRangelandsintheconterminousUnitedStates(figure11-6).TheRPAavailableonNFSlanddoleadtosomekeydifferences.ForPacificCoastandSouthRegionsaccountfornearlyequalexample,downhillskiing/snowboardingisthesecond-mostsharesofvisits;theRPARockyMountainRegionhasthecommonprimaryactivityonNFSlandbutalesscommonlowesttotalvisitationtoStateparksystemlands.Since2009,activitywhenconsideringrecreationonalllands.ThattheRPASouthRegionhasexperiencedthegreatestincreasedifferenceresultsbecausepubliclands,particularlyNFSinStateparkvisitation:an18-percentincreaseoverthelands,providemuchmoredownhillskiingopportunitythanperiod.Overthesametimeframe,Stateparkvisitationintheprivatelands.TherelativepopularityofdifferentrecreationRPAPacificCoastRegionincreasedbyonly2percent.activitiesonNFSlandshasbeenstableoverthelastdecadeormore.Themostcommonrecreationactivities(hiking,Figure11-6.AnnualvisitationtoStateparksystemsbyRPAregionandviewingnature,andskiing/snowboarding)havemaintainedconterminousUnitedStates(CONUS),2009to2017.MostStateparktheirprominenceandthenumberofvisitsforless-commonvisitationregionallyoccursintheNorthRegion,comprisingapproximatelyactivitieshavegenerallyheldsteady.halfofthevisitsfortheconterminousUnitedStates.Morethan60percentofvisitstoNFSlandsaremadebySource:SmithandLeung2019.men—generallyconsistentwiththedemographicpatternsofoutdoorrecreationparticipantsnationally(USDAForestFederalAgencies—RecreationistheprimarywaythatService2020).WhitesaccountforthevastmajorityofvisitsmostpeopleengagewithfederallyownednaturalresourcetotheNFS.Onaverage,NFSrecreationvisitscomefromlands.Therearemorethan900millionvisitseachyearuserswithabove-averageincomesandusersbetweenagestofederallymanagedrecreationlands.TheNPSleadsthe30and60(USDAForestService2020).ThedemographicFederalagenciesinthenumberofrecreationvisitswithmorepatternsofvisitstotheNFShavebeenrelativelystableoverthan316millionvisitseachyear(figure11-7).TheUSDAtime.Onaverage,morethanhalfofvisitscomefromthoseForestServicereceivesabout150millionvisitstoNFSlandswhohavetraveledlessthan50milesfromhome(USDAeachyear.ThenumberofvisitsannuallytoFederallandsForestService2020).Thatpatternisconsistentwiththe(excludingtheACOE)hasincreasedslightlysince2010.ThedistancepeoplecommonlytraveltoengageinoutdoorFWSandtheBLMhadthegreatestpercentageincreases(byrecreationonalllands(OutdoorFoundation2019);however,23and16percent,respectively)overtheperiod,whilethevisitorsoftentravelmuchgreaterdistancestovisituniqueNPSexperiencedthegreatestnominalvisitincrease(aboutNFSrecreationresourcesandmanyNPSdestinations.Most33millionadditionalvisits).outdoorrecreationvisitsonNFSlandsareshort:nearly40TheUSDAForestServiceNationalVisitorUseMonitoringpercentlastlessthan3hours(USDAForestService2020).An(NVUM)Programprovidesthemostcomprehensiveandadditional30percentofvisitslastbetween3and6hours.consistentdataaboutrecreationistsusingFederallands(Leggettetal.2017).ResultsfromtheNVUMProgramcanFigure11-7.Annualvisitationtofederallymanagedoutdoorrecreationprovideinsightintohowrecreationpatternsonfederallyresources.managedlandscomparetonationalrecreationpatterns.Themost-popularoutdoorrecreationactivitiesacrosstheUnitedNote:TheArmyCorpsofEngineers(ACOE)visitestimationprocedurewasrevisedbeginninginStates(seepriorsection)arealsocommononNFSland2014;prioryeardataisnotcomparabletothecurrentapproachusedbyACOE.Dayvisitstothe(USDAForestService2020).Forexample,bothnationallyACOEaremeasuredinunitsequivalenttothevisitsofotheragencies.However,overnightvisitstoandonNFSlands,hikingisthemostcommonrecreationtheACOEaremeasuredinpersonnights,whichwouldyieldahigherrecreationuseestimatethantheactivity.However,thetypesofrecreationopportunitiesvisitsmeasureusedbytheotheragencies.Sources:Chang2020(ACOE);English2020(USDAForestService);Miller2020(NPS,BLM,FWS,andBOR).2020ResourcesPlanningActAssessment11-13UsingCrowd-SourcedandSocialMediaDataToUnderstandRecreationUseCommonapproachestorecreationmonitoring,suchasaboutvisitordistributions,behaviors,andpreferencestrafficcountersandvisitorsurveys,areusefulforgathering(Fisheretal.2018,Sessionsetal.2018,Woodetal.2013).consistent,long-termdataaboutrecreationonpubliclands.VisitorstopubliclandsoftensharedigitalinformationTraditionalapproachescanbetime-consuming,relativelyabouttheirexperienceintheformofphotos,posts,ortripcostly,andchallengingtouse.Agrowingbodyofpeer-logs,someofwhicharegeographicallyspecific.OnerecentreviewedresearchshowsthatvolunteeredgeographicdatastudyexaminingthepromiseandpotentialpitfallsofusingfromsocialmediacancomplementexistinginformationsocialmediatoestimaterecreationaluseintheUnitedStates(Woodetal.2020)foundthatthenumberofsocialFigure11-8.Spatialcoverageofgeotaggedpostsfrommultiplemediapostssharedinalocationcansubstantiallyimprovesocialmediaplatforms(Flickr,Twitter,andInstagram)acrossareasvisitorestimatesatunmonitoredsites.VisitationestimatesinwesternWashingtonandnorthernNewMexico.PointsrepresentarefurtherimprovedwhenmodelsareparameterizedwiththelatitudeandlongitudewhereaFlickrphotograph(purple)oronsitecounts,showingthatalthoughsocialmediapostsdotweet(green)wascreated.ForInstagram,pointsrepresentplacestonotfullysubstituteforonsitedata,theycanbeapowerfulwhichimageswereassignedbyusers(blue).Largerpointsrepresentacomponentofrecreationresearchandvisitormanagement.greaternumberofInstagrampostsfromthelocation.Studieshaveconcludedthattherearepotentialadvantages,butalsolimitations,tomonitoringrecreationwithvolunteeredgeographicinformation.Thespatialandtemporalcoverageofsocialmediamakestheinformationwidelyavailableyear-roundandindependentoflandownership(figure11-8).Nonetheless,socialmediausersareaself-selectedpopulation.Individualsuseavarietyofsocialmediaplatforms,andthecostofdataaccesscanvarybysource.Socialmediadatamaybemostbeneficialforfillinginspatialandtemporalgapsintraditionalrecreationmonitoringprograms,tocaptureuniqueeventsorothersituationsthatmightcausevisitationtodeviatefromthelong-termtrend(Woodetal.2020).Futureresearchisnecessarytounderstandhowvolunteereddatacanbefullyleveragedtoimprovetheaccuracyandefficiencyofrecreationmonitoringefforts.SpencerWood,OutdoorRecreationandDataLab,UniversityofWashingtonEmmiLia,OutdoorRecreationandDataLab,UniversityofWashingtonSamanthaWinder,OutdoorRecreationandDataLab,UniversityofWashingtonPrivateLands—UnderstandingtheamountofrecreationForexample,morethanhalfoftheforestlandowneduseinvolvingrecreationresourceshelpsmanagers,byindividualsandfamiliesisusedforrecreationbythepolicymakers,andresearchersassesstherelativeowners(Butleretal.2020).Further,about5percentofcontributionofdifferenttypesofrecreationresourcesintheforestlandareaownedbyindividualsandfamiliesismeetingrecreationdemand.Unfortunately,recreationuseofavailabletothepublicforrecreation(Butleretal.2020).privatelandshasnotbeenquantified.AlthoughthereisnoThemostcommonrecreationaluseofforestlandsownedcomprehensiveestimateoftheamountofoutdoorrecreationbyindividualsandfamiliesishunting,followedbyfishing,useonprivatelands,surveysofoutdoorrecreationistsandhiking/walking,andoff-highwayvehiclerecreation.Privatelandownersindicatethatoutdoorrecreationistsareindeedlandsareakeyrecreationproviderforsomeactivitiesandusingprivatelandstorecreate(USDAForestService2012).insomeregions.Forexample,acrosstheUnitedStates,and11-14FutureofAmerica’sForestsandRangelandsparticularlyintheRPASouthRegion,privatelandrecreationshareoftheU.S.populationparticipatinginrecreationresourcesareimportantplacesforhunting(USDAForestincreasedby2percentagepoints(to53percent)andaboutService2012).Privatelandrecreationmaybeinformal,7.1millionpeople(OutdoorFoundation2021a).Thosesuchasindividualsrecreatingonlandsownedbyfamily2020participantsrenewingtheirparticipationinoutdoororfriends,ormoreformalsuchasindividualspurchasingrecreationorengagingforthefirsttimeweremostlikelypermitstorecreateonlandsownedbyforestindustry(e.g.,toparticipateinwalking/hiking(47percent)followedbyMingieetal.2017).outdoorrunning/jogging(28percent)andoutdoorbicycling(26percent)(OutdoorFoundation2021b).AbouthalfofCOVID-19Pandemic—Thepandemic,theassociatedthenewlyengagingparticipantsin2020reportedthattheyreductioninotherleisureopportunities,andthedesirehadpreviouslyengagedintheirrecreationactivityandweretoengageinactivitiesthatseeminglyposedlimitedreturning(OutdoorFoundation2021b).AlthoughthenumberCOVIDexposureriskledtoincreasedparticipationandofparticipantsinoutdoorrecreationincreasedin2020,itengagementinoutdoorrecreationin2020.In2020,theappearedthatparticipantsdidnotchangethenumberoftimesCOVID-19andRecreationVisitationtoNFSUnitsTheCOVID-19pandemichadwide-rangingandTodevelopanaccuratenationalvisitestimatefor2020,substantialeffectsontheamountofrecreationvisitationweneededtoaccountforthelikelyincreasedvisitationtoNationalForestSystem(NFS)landsduringmostofatunitsnotsampledin2020.Wecalculatedthepercent2020.NationalVisitorUseMonitoring(NVUM)samplingchangeinvisitationbetweenthe2015and2020observedoccurredon24NFSreportingunitsspreadacrosstheonthe2020sampleforestsinthelasthalfofthefiscalcountryduringfiscalyear2020(October2019toOctoberyear,adjustedforanormalgrowthrateovertime,and2020).ThesesameunitswerepreviouslysampledinappliedthatpercentagechangetotheNFSunitsthat2015,aspartofthe5-yearNVUMcycle.Theobservedwerenotsampledin2020.Intotal,theNFSsawabout18differencesinvisitationbetweenthe2015and2020millionmorevisits(a12-percentincrease)in2020thaninsamplesweresimilaracrossthesampledunits.2019.Theincreaseinuseiswellabovetheyear-to-yearincreasesobservedinrecentyears(table11-9).Weobservedagenerallossinvisitationatdevelopedsites,primarilyowingtoshortenedseasonsduetoCOVID-19Table11-9.NVUM-basedestimatesofrecreationvisits(millions)closures.AnumberofdownhillskiareasclosedfortheironNFSlandsacrossfoursitetypesforFY2019andFY2020,withspringseason,andmanysawlargereductionsinsummercomputeddifferences(millions)betweenthetwotimeperiods.use.Visitorcenters,picnicareas,andothertypesofdayusefacilitiesthatnormallysupportconcentratedvisitationDayusedevelopedFY2019FY2020Changehadclosuresand/oruselimitationsfromApril2020sites(millions)(millions)from2019onwards.Inmanypartsofthecountry,largercampgroundsOvernightuse(millions)openedlaterintheyear,andgroupcampsiteshadverydevelopedsites77.474.9littleusage.Useofsmallerday-usesitesandcampgrounds,Generalforest-2.5however,reboundedsubstantiallystartinginmid-summer.areas14.212.9Wilderness-1.3Incomparison,visitationtodispersedsettingsboomedasTotalsitevisits93.2115.9peoplesoughtoutdoorexperiencesinuncrowdedspaces.NationalForest9.016.0+22.7Visitationratestoundevelopedgeneralforestsettingsvisits193.9219.7+7.0rosebymorethan50percentinApriltoOctober2020,150.0168.2+25.8comparedtoobservedvisitationin2015.Accesspoints+18.2thatnormallyseelowerlevelsofusesawthegreatestincreasesinvisitation.Incontrast,themost-popularFY=fiscalyear;NFS=NationalForestSystem;NVUM=NationalVisitorUseMonitoring.locationshadonlymoderatelevelsofincreasedvisitation.VisitationratestoWildernessaccesspointsweremoreDonEnglish,USDAForestService,WashingtonOfficethandoubletheratesobservedin2015.ThegreatestproportionalincreasesinvisitationoccurredatlessEricM.White,USDAForestService,PacificNorthwestpopularlocations.ResearchStation2020ResourcesPlanningActAssessment11-15theyengagedinrecreationin2020(OutdoorFoundation2020a).Tobesuccessful,recreationmanagersandpolicymakersplanTherewereinconsistentpatternsinthechangeinvisitationtoandmanageforbothcurrentandanticipatedfuturerecreationFederallandsin2020.CombinedvisitationtoallNPSunitsdemand.Understandinghowrecreationdemandmightchangein2020declinedby26percent,butvisitationat15unitssetcanprovideinsightintohowpeoplewillinteractwithnaturalrecordsin2020(NPS2021).FortheUSDAForestService,resourcesinthefutureandinformshort-andlong-termvisitationincreasedbyabout12percent,butthoseincreasesplanningaboutrecreationresourceinvestment.Asinpriorwereconfinedtodispersedrecreationopportunities,suchastrailsRPAAssessments,weprojectrecreationdemand50years(seethesidebarCOVID-19andRecreationVisitationtoNFSintothefuture.Inthisassessment,weuseabaseyearof2012Units).Althoughitisunknownwhatwillhappen,thereislittletoandprojectdemandforeachdecadeto2070.WedevelopsuggestthatCOVID-inducedrecreationpatternswillinfluenceestimatesofhowmanypeopleareprojectedtoengageinlong-term(decadeshence)patternsinrecreationparticipation.outdoorrecreationinthefuture,alongwiththefrequencyofAbout25percentoftheneworrenewingparticipantsin2020theirengagement.reportedtheirintentiontodiscontinuerecreatinginfutureyears(OutdoorFoundation2021b).Further,althoughtheProjectionMethodssignificanteventsofthefirstdecadesofthe21stcentury(e.g.,theSeptember11thterroristattacks,theGreatFinancialCrisis,AsinpriorRPAAssessments,wedevelopprojectionsofandspikesingasolineprices)didyieldobservablechangesinfuturerecreationparticipationandconsumptionforasetrecreationpatterns,thosechangeswereultimatelytransitory,ofoutdoorrecreationactivitiesandactivityaggregatesandpatternsreturnedtobaselinetrends.However,oneimportant(hereafteractivity(ies))(table11-10).AsidefromnatureunknowniswhetheranoverlylongCOVIDpandemic,drivenviewing,whichincludesbirding,allotheractivitiesarebyvaccinereluctance,oracycleofrecurringpandemicsovermutuallyexclusive,andrecreationistsmayengageinoneorthecomingdecadescouldyieldsustained,long-termchangesinmoreatleastoncewithintheyear.Theactivitysetusedhererecreationpatterns.differsslightlyfromthoseusedinpriorRPAAssessments(e.g.,Bowkeretal.2012).ThesetofactivitiesweuseProjectionofFutureRecreationinthisassessmentalignsbetterwiththoseconsideredbyDemandtheOutdoorFoundationintheirstudiesofU.S.outdoorrecreationengagement(e.g.,OutdoorFoundation2019)❖ModestchangesinpercapitaparticipationareandtheactivitysetusedbytheUSDAForestServiceintheirrecreationmonitoringprogram,NationalVisitorUseprojectedforalmostallactivities,withaslightMonitoring.InthisRPAAssessment,wetreatcampinginmajorityofactivitiesprojectedtoexperiencedevelopedcampgroundsasauniqueindividualactivity.decreasedpercapitaparticipationratesintheConversely,wemergethepreviouslyuseddevelopedsitecomingdecades.useaggregate(minusdevelopedsitecamping)andthepreviouslyusedvisitinginterpretativesitesaggregateinto❖Downhillskiingandsnowboarding,motorizedwaterasingledevelopedsiteuseaggregate.Finally,aftertreatingmountainbikingasanindividualactivity,weremovedfromuse,equestrianridingontrails,andmountainbikinganalysistheremaining“challengeactivities”consideredinareprojectedtoseemoderateincreasesinperpriorassessments,anaggregateofmountainclimbing,rockcapitaparticipationlevelsinmostscenarios,whileclimbing,andcaving.huntingandmotorizedsnowuseareprojectedtohavethelargestdeclinesinpercapitaparticipationWefollowedtheapproachusedinthe2010RPAAssessmentinfuturedecades.andtheUpdatetothe2010RPAAssessmenttoprojectfuturerecreationdemand(AskewandBowker2018,Bowkeret❖Thenumbersofparticipantsanddaysofal.2012).Foreachoutdoorrecreationactivity,weprojectbothfutureparticipationandconsumption.Participationisaengagementareprojectedtoincreaseundermostmeasureofhowmanypeopleareengagedineachrecreationscenariosformostrecreationactivities,primarilyactivity;consumptionisameasureofthemagnitudeofattributabletoprojectedpopulationgrowth.recreationoccurrencesforthatactivity.Theformerprovidesinsightintohowpopularorcommonarecreationactivityis❖Developedsiteuse,swimming,anddayhikingamongthepopulation,andthelattercanprovideinformationonthenumberofrecreationoccurrencesthatmanagersandareprojectedtohavethegreatestnumbersofpolicymakersmightexpect.participants.Toprojectfutureparticipationinoutdoorrecreation,we❖Lowerlevelsofatmosphericwarminggenerallyleaddevelopedstatisticalmodelsofanticipatedpercapitatogreaterparticipantnumbers.❖ProjecteddeclinesinparticipantsandconsumptionaregenerallyconfinedtothelowpopulationgrowthandeconomicdevelopmentscenarioandtheRPANorthRegion.11-16FutureofAmerica’sForestsandRangelandsTable11-10.Recreationactivitiesandassumedinitialoutdoorrecreationperparticipantwiththeprojectionsofnumberoffutureengagementin2012.participantstoarriveatanestimateoftotalprojectedconsumption(measuredintotalparticipantdaysperyear).PopulationModelsofpercapitaparticipationandconsumptionareparticipatingDaysofestimatedforeachactivityandforalladults(16andparticipationolder),withineachRPAregion.Thenational-levelfiguresActivityoractivitygrouping(percentofthereportedherearedevelopedfromaggregatingtheregional-U.S.population,eachyearlevelresults,afteraccountingfordifferencesinregionalpopulations.Ourprojectionsoffuturedemanddonot16andover)12.0includeindividualslivinginAlaska,Hawaii,ortheU.S.7.7territoriesbecausewelackdatatocharacterizerecreationDevelopedsiterecreationuseofthosepopulations.Modelsincludevariablesto15.5describeanticipatedsocio-demographiccharacteristicsofDevelopedsiteuse—family37.614.2futurepopulationsaswellasvariablesrelatedtoregionalrecreationresourcesupplyandclimaticconditions.Modelgatherings,picnicking,etc.15.3variablesusedtodescribeclimaticconditionsinclude1.5seasonalmaximumorminimumtemperature,seasonalCampingindevelopedcampgrounds10.219.8precipitation,andpotentialevapotranspiration(awater12.7lossmeasurethatcombinesinformationabouttemperature,Viewing/photographingnature13.3humidity,sunlight,andwind).FollowingAskewand16.4Bowker(2018),eachactivitymodelincorporatesone,bestViewingnature—relatedtofauna,7.76.7statisticallyperforming,climatevariable.Moredetailedregional-levelresultsandmodelspecificationswillbeflora,ornaturalsettings16.0providedinfutureRPAAssessmentsupportingdocuments.18.9Bbiirrddsiang—viewingorphotographing4.9Weprojectrecreationdemandforthefourfuturescenarios6.4recognizedinthisRPAAssessment(seethesidebarRPANon-motorized,undevelopedactivities5.3Scenarios).Takenindividually,thescenariosprovideinformationonthepotentialoutcomesinrecreationdemandDayhiking12.512.0underaspecificsetoffutureconditions.Collectively,our6.0recreationprojectionsunderthefourscenariosprovidePrimitiveareaactivities—insightintothepotentialrangeofdemandforoutdoorrecreationinthefuture.Pairwisecomparisonsbetweenundevelopedareacamping,2.8scenariosoffertheopportunitytoisolatetheinfluencesofchangingclimaticandsocioeconomicconditions.Becausebackpacking,visitingWildernesstheassumedsocioeconomictrajectoriesintheLowModerate(LM)andHighModerate(HM)scenariosareverysimilarMountainbiking2.5(Langneretal.2020),differencesinrecreationoutcomesbetweenthosescenariosprimarilytracetodifferentEquestrianridingontrails1.4projectionsoffutureclimaticchangeasinfluencedbydifferentlevelsofatmosphericwarming(seethesidebarMotorizedactivitiesRPAScenarios).Thus,wecomparetheprojectionsoffuturerecreationdemandundertheLMandHMscenariostoMotorizedwateruse11.1assesstheinfluenceofatmosphericwarmingonrecreationdemand.Likewise,becausetheassumedfutureatmosphericMotorizedoff-roaduse8.6warmingconditionsareidenticalintheHighLow(HL)andHighHigh(HH)scenarios(Langneretal.2020),anyMotorizedsnowuse—snowmobiling2.5differencesinrecreationoutcomesreflecttheinfluenceofsocioeconomicchangeonrecreationdemand.Thus,weHuntingandfishingcomparetheprojectionsoffuturedemandundertheHLandHHscenariostoassesstheinfluenceofsocioeconomicFishing—anadromous,cold-water,12.5changeonrecreationdemand.saltwater,warm-waterHunting—smallgame,biggame,5.1migratorybird,otherNon-motorizedwinteractivitiesDownhillskiingandsnowboarding6.8Cross-countryskiingandsnowshoeing3.8Non-motorizedwateractivitiesSwimming—swimming,snorkeling,19.6andscubadivingFloating—canoeing,kayaking,4.1orraftingaBirdingparticipationratesanddaysofparticipationarealsoincorporatedinthevaluesforviewingnature.Source:InitialvalueswerebasedontheOutdoorIndustryAssociation(OutdoorFoundation2018),inconjunctionwiththeNationalSurveyonRecreationandtheEnvironment(NSRE).Thesewereobtainedeitherdirectly,byactivitymatchingbetweentheOutdoorFoundationandNSRE,orindirectly,byformulatingOutdoorFoundation-basedscalarsforadjustmentsofNSREestimates(formoreconservativeestimation).participationforeachactivity.Thepercapitaparticipationratesidentifytheshareoftherespectiveadultpopulationsengagingineachactivity.Wecombinedthosepercapitaparticipationrateswithprojectionsoffuturepopulationtoarriveattheprojectednumberoffutureparticipants.Toprojectfutureconsumptionofoutdoorrecreation,wedevelopedstatisticalmodelstoprojecthowmanydaysperyearthoseparticipatinginaspecificactivitywillengageinthatactivity.Wecombinedthoseaveragedays2020ResourcesPlanningActAssessment11-17ActivityParticipationRatesandparticipationratein2012was10percent,theresultingindexedparticipationratewouldbe0.50.ThemarkersonthetheInfluenceofFutureClimateandgraphrepresentthepairwisevaluesofprojectedparticipationfor2070betweenScenariosS1andS2.ThestarmarkerSocioeconomicPathwaysrepresentsthecomparisonbetweenscenariosofthemeanindexedparticipationrateacrossthefiveclimateprojections;OurprojectionsoffutureparticipationratesrepresentthetheothershapesrepresentcomparisonsfortheindividualshareoftheU.S.populationage16andolderexpectedtoclimateprojections(seethesidebarRPAScenarios).Aparticipateinanactivityatleastonceayearundereachofmarkerlocatedabovethesoliddiagonalline(areaAofthetheRPAscenarios.Inthisanalysis,wefocusonprojectionsgraph)indicatesthatprojectedparticipationratesin2070for2070toconsidertherelativeeffectsofclimateandaregreaterinScenarioS1comparedtoScenarioS2forthatsocioeconomicchangeonpercapitaparticipation(resultsclimatemodel.Amarkerlocatedbelowthesoliddiagonallinefor2040areavailableinthenextsectionofthischapter).(areaBofthegraph)indicatestheopposite.ThedistancetheForeachactivityandscenario,wecalculatedthemeanmarkerislocatedfromthesolidlinedepictsthemagnitudeindexedparticipation(2070relativeto2012)acrossthefiveofthedifferenceinprojectedparticipationratesbetweentheclimateprojections.Wethencomparedthosemeanindexedtwoscenarios:markersnearestthediagonallineindicateparticipationvaluesbetweenpairedRPAscenarios(i.e.,smallerdifferencesbetweenthescenarios.MarkersabovetheLMversusHM,HLversusHH)toclassifyeachactivityassmallerdashedhorizontalline(areaCofthegraph)indicateexhibitingrelativesensitivityprimarilytofutureclimate,theprojectedparticipationratein2070isgreaterthanthefuturesocioeconomicconditions,both,orneither.Acrosstherateobservedin2012underScenarioS1.Markerslocated17activitiesconsideredhere,weprojectthatbetween2012belowthesmallerdashedhorizontalline(areaDinthegraph)and2070,sixactivitieswillexperienceanincreaseinperindicatetheprojectedparticipationratein2070islowerthancapitaparticipation,ninewillexperienceadecline,andtwotherateobservedin2012underScenarioS1.Areasoneitherwillseelittlechange(table11-11).Projectedparticipationsideofthelongerdashedverticalline(EandFinthegraph)insixofouractivitiesexhibitedsensitivitytodifferenceshavethesamemeanings,butforScenarioS2.ItispossibleinthesocioeconomicchangeinourscenariosandsixthatresultsunderbothscenariosS1andS2mayjointlyyieldweresensitivetobothsocioeconomicchangeandclimaticprojectionsoffutureparticipationthatarehigher(orlower)change.Fiveactivitiesexhibitedlittlesensitivitytoeitherthanthatobservedin2012.socioeconomicorclimaticchange.AsidefromassumedlevelofatmosphericwarmingassociatedwiththeRPAAtmosphericWarmingasPrimaryDriver:LMversusscenario,projectedpercapitaparticipationforseveralofourHM—Noactivitiesexhibitedresponsivenessprimarilyactivitieswassensitivetooneormoreclimateprojections.tochangingclimateconditionsalone,representedbytheWhenprojectedparticipationratesweresensitivetoclimatedifferencesinatmosphericwarmingbetweenourLMandprojection,higherratesofparticipationwerefrequentlyassociatedwiththeleastwarmclimateprojectionandlowerFigure11-9.ExamplecomparisonofrelativepercapitaparticipationratesofparticipationwerefrequentlyassociatedwiththehotindicesinexamplescenariosS1andS2.SeetextfordescriptionsoflettersAclimateprojection.throughF.WeusetwographsforeachactivitytoexploretheParticipationRateIndices:S1versusS2sensitivitiesoftheactivitytotheinfluenceofchangingclimate(LMversusHM)andsocioeconomicconditions1.3(HLversusHH).Ingraphingfutureoutlooksforagivenactivity,theverticalandhorizontalaxescorrespondtopaired1.2RPAscenarios(S1andS2,respectively);eachgraphdepictsacomparisonofindexedpercapitaparticipationratein1.12070underthescenariosjointly(figure11-9).TheindexedparticipationratesarecomputedrelativetotheparticipationScenarioS11.0rateobservedinthebaseyear2012,andvaluesreflectapercentagechangefromthe2012estimate.Avaluegreater0.9than1.0indicatesahigherprojectedparticipationratethanthatobservedin2012.Forexample,iftheprojected0.8participationratein2070was20percentandtheobservedparticipationratein2012was15percent,theresulting0.70.80.91.01.11.21.3indexedparticipationratewouldbe1.33.Conversely,a0.7WetMiddleMeanvaluelessthan1.0indicatesalowerprojectedparticipationScenarioS2ratein2070relativeto2012.Forexample,iftheprojectedDryparticipationratein2070was5percentandtheobservedLeastWarmHot11-18FutureofAmerica’sForestsandRangelandsTable11-11.Projectedchangesinpercapitaparticipationbetween2012and2070andtherelationshipofinfluencingfactorstoparticipationrate.ProjectedchangeResponsivenessInfluenceofInfluenceofhigherClimateprojection(s)Climateprojection(s)tosocioeconomichigherlevelsoflevelsofatmosphericleadingtohighestleadingtolowestinpercapitachangeorclimacticsocioeconomicwarmingonperprojectedpercapitaprojectedpercapitachangegrowthonpercapitacapitaparticipationparticipationparticipationActivityoractivitygroupingparticipationparticipationbetween2012and2070DevelopedsiterecreationDevelopedsiteuse—familyNeithergatherings,picnicking,etc.CampingindevelopedSocioeconomicDryLeastwarmcampgroundschangeViewing/photographingnatureViewingnature—relatedtoNeitherfauna,flora,ornaturalsettingsBirding—viewingorNeitherLeastwarmHotphotographingbirdsaNon-motorized,undevelopedactivitiesDayhikingBothLeastwarm,WetHotPrimitiveareaactivities—undevelopedareacamping,NoneLeastwarmHot,Middlebackpacking,visitingWildernessMountainbikingBothEquestrianridingontrailsSocioeconomicHot,MiddlechangeMotorizedactivitiesMotorizedwateruseSocioeconomicHot,MiddleLeastwarmchangeMotorizedoff-roaduseSocioeconomicchangeMotorizedsnowuse—BothLeastwarmHot,DrysnowmobilingHuntingandfishingNoneMiddleHotFishing—anadromous,cold-water,saltwater,warm-waterSocioeconomicHunting—smallgame,biggame,changemigratorybird,otherNon-motorizedwinteractivitiesSocioeconomicDownhillskiingandchangesnowboardingCross-countryskiingandBothLeastwarmsnowshoeingNon-motorizedwateractivitiesBothWet,LeastwarmHotSwimming—swimming,snorkeling,andscubadivingBothWet,LeastwarmFloating—canoeing,kayaking,orraftingaBirdingparticipationratesanddaysofparticipationarealsoincorporatedinthevaluesforviewingnature.=unambiguousincreaseordecreaseinprojectedpercapitaparticipation,=increaseordecreaseinpercapitaparticipationinmostprojectioncases,=noclearoutcomeorrelationship.HMscenarios.Sixactivities(discussedinalatersection)motorizedwateruse,motorizedoff-roaduse,hunting,andexhibitedresponsivenesstobothatmosphericwarminganddownhillskiingandsnowboardingexhibitresponsivenesschangingsocioeconomicconditions.Further,manyactivitiestothelevelsofpopulationandeconomicgrowthbut(discussedinsubsequentsections)exhibitedresponsivenessarerelativelyunchangedbydifferinglevelsoffuturetodifferentclimatefutures(e.g.,wet,leastwarm,hot)withinatmosphericwarming(demonstratedbyincreaseddistancetheindividualRPAscenarios.frommarkerstodiagonallinefortheHL/HHfigurerelativetotheLM/HMfigure;figure11-10).ProjectedparticipationEconomicDevelopmentandPopulationGrowthasratesin2070fordevelopedsitecamping,motorizedoff-roadPrimaryDriver:HLversusHH—Participationratesuse,andhuntingareallgreaterundertheHLscenariothanindevelopedsitecamping,equestrianridingontrails,2020ResourcesPlanningActAssessment11-19Figure11-10.Projectedpercapitaparticipationin2070indexedto2012,comparingRPAscenariosLMwithHM(climatechange,left)andHLwithHH(socioeconomicchange,right)for(a)developedsitecamping,(b)equestrianridingontrails,(c)motorizedwateruse,(d)motorizedoff-roaduse,(e)hunting,and(f)downhillskiingandsnowboarding.InfluenceofClimateChangeforaInfluenceofSocioeconomicChangeforDevelopedSiteCampingDevelopedSiteCampingInfluenceofClimateChangeforInfluenceofSocioeconomicChangeforEquestrianRidingonTrailsbEquestrianRidingonTrails1.41.31.21.11.00.90.80.70.7LLeWasWt0W.w8aWrmH0H.o9HtDDr1y.0WWewt1.1MMidMdMl1e.2MMeea1an.n31.4LM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.11-20FutureofAmerica’sForestsandRangelandsFigure11-10continued.Projectedpercapitaparticipationin2070indexedto2012,comparingRPAscenariosLMwithHM(climatechange,left)andHLwithHH(socioeconomicchange,right)for(a)developedsitecamping,(b)equestrianridingontrails,(c)motorizedwateruse,(d)motorizedoff-roaduse,(e)hunting,and(f)downhillskiingandsnowboarding.InfluenceofClimateChangeforcInfluenceofSocioeconomicChangeforMotorizedWaterUseMotorizedWaterUseInfluenceofClimateChangeforInfluenceofSocioeconomicChangeforMotorizedOff-RoadUsedMotorizedOff-RoadUse1.41.31.21.11.00.90.80.70.7LLeWasWt0W.w8aWrmH0H.o9HtDDr1y.0WWewt1.1MMidMdMl1e.2MMeea1an.n31.4LM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.2020ResourcesPlanningActAssessment11-21Figure11-10continued.Projectedpercapitaparticipationin2070indexedto2012,comparingRPAscenariosLMwithHM(climatechange,left)andHLwithHH(socioeconomicchange,right)for(a)developedsitecamping,(b)equestrianridingontrails,(c)motorizedwateruse,(d)motorizedoff-roaduse,(e)hunting,and(f)downhillskiingandsnowboarding.InfluenceofClimateChangeforInfluenceofSocioeconomicChangeforHuntingeHuntingInfluenceofClimateChangeforInfluenceofSocioeconomicChangeforDownhillSkiing/SnowboardingfDownhillSkiing/Snowboarding1.41.31.21.11.00.90.80.70.7LLeWasWt0W.w8aWrmH0H.o9HtDDr1y.0WWewt1.1MMidMdMl1e.2MMeea1an.n31.4LM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.11-22FutureofAmerica’sForestsandRangelandsHHbecausetheimprovedeconomicwell-beingandgreaterswimming,anddayhikingareresponsivetobothlevelsofpopulationgrowthoftheHHscenarioresultinlowerfutureatmosphericwarmingandpopulationgrowthandeconomicratesofpercapitaparticipationinthoseactivities.Thisdevelopment(figure11-11)(depictedbyprojectionsofftherelationshipismostpronouncedforhunting.Incontrast,diagonallineinboththeLM/HMandHL/HHgraphs).Forimprovedeconomicwell-beingandincreasedpopulationalloftheseactivities,percapitaparticipationisprojectedgrowthleadtohigherratesofparticipationinequestriantobegreaterunderloweratmosphericwarming(theLMridingontrails,motorizedwateruse,anddownhillskiingscenariocomparedtotheHMscenario).Inaddition,andsnowboarding.eachactivityhashigherlevelsofprojectedpercapitaparticipationinthehigh-growthHHscenariocomparedtoAlthoughtheprojectionsofpercapitaparticipationforthelow-growthHLscenario.theseactivitiesdonotexhibitmuchresponsivenesstochangesinthelevelsoffutureatmosphericwarming(LMAlthoughtheloweratmosphericwarmingintheLMversus.HMscenarios),projectedpercapitaparticipationscenarioleadstohigherprojectedpercapitaparticipationratesfordevelopedsitecamping,equestrianridingonrelativetotheHMscenarioforeachactivity,thepotentialtrails,andmotorizedwateruseexhibitresponsivenessrangeinfutureclimatealtersthedegreetowhichtheretoindividualclimateprojections(depictedbythemoreisapositiveinfluenceonpercapitaparticipation(i.e.,dispersedparticipationprojectionsforthoseactivities).Forthedistancefromthediagonalline).Fordayhiking,thedevelopedsitecamping,projectedparticipationratesaremostpronounceddifferencesbetweenthelowerandhighhighestwhenusingthedryprojectionandlowestundertheclimaticchangescenariosarefoundwhenusingthewetleastwarmprojection.Forequestrianridingandmotorizedandthehotclimateprojections;formountainbiking,wateruse,thehotandmiddleprojectionsresultinperthewetanddryclimateprojectionsyieldthegreatestcapitaparticipationratesthataremeaningfullyhigherthandifferences.Finally,thedryclimateprojectionproducestheotherclimateprojectionsacrossallRPAscenarios.Forthegreatestdifferencesinprojectedparticipationincross-motorizedwateruse,theleastwarmprojectionyieldsapercountryskiingandsnowshoeingandmotorizedsnowuse.capitaparticipationratethatismeaningfullylowerthanotherclimateprojectionsacrossallRPAscenarios.PerCapitaParticipationRelativeto2012—Forthissetofactivities,thereishighvariationacrossthe20RPAPerCapitaParticipationRelativeto2012—Projectedperscenario-climatefuturesinhowprojectedpercapitacapitaparticipationinequestrianridingontrails,motorizedparticipationin2070comparesto2012.Foreveryactivitywateruse,anddownhillskiingandsnowboardingisexceptmotorizedsnowuse,atleasttwoscenario-climateprojectedtobegreaterin2070thanin2012acrossallfuturesprojectgrowthinpercapitaparticipationbetweenscenarios(depictedbyprojectionsgreaterthan1.0).The2012and2070(i.e.,participationvaluesgreaterthan1.0).greatestincreasesinpercapitaparticipationareprojectedFormountainbiking,anincreaseinpercapitaparticipationfordownhillskiingandsnowboardingundertheHHisprojectedinallcombinationsexceptHL-wet.Cross-scenario,withparticipationratespotentiallyuptoaroundcountryskiingandsnowshoeingaggregateexhibits140percentofobserved2012participation.Projectedperpathwaystogrowthinpercapitaparticipation,relativetocapitaparticipationindevelopedsitecamping,motorized2012,underLM-leastwarmandHH-leastwarm.Forfloatingoff-roaduse,andhuntingareprojectedtobelowerinandswimming,thegreatestparticipationratescorrespond2070than2012acrossallscenariosandallprojections.tothewetandleastwarmclimateprojections(acrossallHuntingisprojectedtoexperiencethegreatestpercapitascenarios),eitherbygreatestincreaseorslowestdeclineparticipationdeclines,withprojectedrelative2070perfrom2012.Finally,projectedpercapitaparticipationincapitaparticipationaslowas60percent(underHH-middledayhikingexhibitsincreasesinallscenario-climatefuturesandHH-hot)andashighas80percent(underHL-dryandexceptHH-hot,LM-leastwarm,andLM-wet.ThesmallestHL-leastwarm)ofobserved2012participationrates.reductioninparticipationinmotorizedsnowuse(93percentof2012participation)isprojectedforLM-leastwarm;theResponsivetoBothDrivers—Projectionsofperleastwarmclimateprojectionyieldsthehighestmotorizedcapitaparticipationinmountainbiking,cross-countrysnowuseparticipationratesacrossallfourscenarios.skiingandsnowshoeing,motorizedsnowuse,floating,2020ResourcesPlanningActAssessment11-23Figure11-11.Projectedpercapitaparticipationin2070indexedto2012comparingRPAscenariosLMwithHM(climatechange,left)andHLwithHH(socioeconomicchange,right)for(a)mountainbiking,(b)cross-countryskiingandsnowshoeing,(c)motorizedsnowuse,(d)floating,(e)swimming,and(f)dayhiking.InfluenceofClimateChangeforaInfluenceofSocioeconomicChangeforMountainBikingMountainBikingInfluenceofGHGEmissionsforInfluenceofSocioeconomicChangeforDevelopedSiteCampingbCross-CountrySkiing/Snowshoeing1.41.31.21.11.00.90.80.70.7LLeWasWt0W.w8aWrmH0H.o9HtDDr1y.0WWewt1.1MMidMdMl1e.2MMeea1an.n31.4LM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.11-24FutureofAmerica’sForestsandRangelandsFigure11-11continued.Projectedpercapitaparticipationin2070indexedto2012comparingRPAscenariosLMwithHM(climatechange,left)andHLwithHH(socioeconomicchange,right)for(a)mountainbiking,(b)cross-countryskiingandsnowshoeing,(c)motorizedsnowuse,(d)floating,(e)swimming,and(f)dayhiking.InfluenceofClimateChangeforcInfluenceofSocioeconomicChangeforMotorizedSnowUseMotorizedSnowUseInfluenceofClimateChangeforInfluenceofSocioeconomicChangeforFloatingdFloating1.41.31.21.11.00.90.80.70.7LLeWasWt0W.w8aWrmH0H.o9HtDDr1y.0WWewt1.1MMidMdMl1e.2MMeea1an.n31.4LM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.2020ResourcesPlanningActAssessment11-25Figure11-11continued.Projectedpercapitaparticipationin2070indexedto2012comparingRPAscenariosLMwithHM(climatechange,left)andHLwithHH(socioeconomicchange,right)for(a)mountainbiking,(b)cross-countryskiingandsnowshoeing,(c)motorizedsnowuse,(d)floating,(e)swimming,and(f)dayhiking.InfluenceofClimateChangeforeInfluenceofClimateChangeforSwimmingDayHikingInfluenceofSocioeconomicChangeforInfluenceofSocioeconomicChangeforDayHikingSwimmingf1.41.31.21.11.00.90.80.70.7LLeWasWt0W.w8aWrmH0H.o9HtDDr1y.0WWewt1.1MMidMdMl1e.2MMeea1an.n31.4LM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.11-26FutureofAmerica’sForestsandRangelandsNoEvidenceofClearDriver—Developedsiteuse,viewingPerCapitaParticipationRelativeto2012—Projectednature,fishing,primitivearearecreation,andbirdingexhibitparticipationin2070indevelopedsiteuseandviewingminimalresponsetoalternatelevelsofatmosphericwarmingnaturearelargelyunchangedfromobserved2012oreconomicdevelopmentandpopulationgrowth(figure11-participation.Slightdeclinesinfishingparticipationare12).However,forfishingandbirdingtherearesomelargerprojectedforallscenario-climatefuturesexceptHL-middle.differencesinindexedparticipationratesbetweentheLMFishingparticipationdeclinesareprojectedtobegreatestandHMscenariosforafewindividualclimateprojections.underthehotclimateprojection.Similarly,thehotandUnderthehotandwetclimateprojections,participationmiddleclimateprojectionsleadtothelargestdeclinesininbirdingisprojectedtobedistinctlyhigherintheLMparticipationinprimitivearearecreation.ProjecteddeclinescomparedtotheHMscenario.Conversely,underthemiddleforthatactivityaresmallestundertheleastwarmclimateclimateprojection,birdingparticipationishighestunderprojection.ParticipationinbirdingisprojectedtorangefromtheHMscenario,countertothepatternforthatactivityinlargelyunchangedfrom2012inLM-wettouptoa9-pointanyotherclimateprojection.Forfishing,theHMscenariolossunderthehotclimateprojection.producesslightlyhigherparticipationovertheLMscenarioinallclimateprojections,butthisdifferenceismorepronouncedunderthemiddleclimateprojection.Figure11-12.Projectedpercapitaparticipationin2070indexedto2012comparingRPAscenariosLMwithHM(climatechange,left)andHLwithHH(socioeconomicchange,right)for(a)developedsiteuse,(b)viewingnature,and(c)fishing,(d)primitiveareause,and(e)birding.InfluenceofClimateChangeforInfluenceofSocioeconomicChangeforDevelopedSiteUseaDevelopedSiteUse1.41.31.21.11.00.90.80.70.7LLeWasWt0W.w8aWrmH0H.o9HtDDr1y.0WWewt1.1MMidMdMl1e.2MMeea1an.n31.4LM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.2020ResourcesPlanningActAssessment11-27Figure11-12continued.Projectedpercapitaparticipationin2070indexedto2012comparingRPAscenariosLMwithHM(climatechange,left)andHLwithHH(socioeconomicchange,right)for(a)developedsiteuse,(b)viewingnature,and(c)fishing,(d)primitiveareause,and(e)birding.InfluenceofClimateChangeforInfluenceofSocioeconomicChangeforViewingNaturebViewingNatureInfluenceofClimateChangeforInfluenceofSocioeconomicChangeforFishingcFishing1.41.31.21.11.00.90.80.70.7LLeWasWt0W.w8aWrmH0H.o9HtDDr1y.0WWewt1.1MMidMdMl1e.2MMeea1an.n31.4LM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.11-28FutureofAmerica’sForestsandRangelandsFigure11-12continued.Projectedpercapitaparticipationin2070indexedto2012comparingRPAscenariosLMwithHM(climatechange,left)andHLwithHH(socioeconomicchange,right)for(a)developedsiteuse,(b)viewingnature,and(c)fishing,(d)primitiveareause,and(e)birding.InfluenceofClimateChangefordInfluenceofSocioeconomicChangeforPrimitiveAreaUsePrimitiveAreaUseInfluenceofClimateChangeforInfluenceofSocioeconomicChangeforBirdingeBirding1.41.31.21.11.00.90.80.70.7LLeWasWt0W.w8aWrmH0H.o9HtDDr1y.0WWewt1.1MMidMdMl1e.2MMeea1an.n31.4LM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.2020ResourcesPlanningActAssessment11-29ParticipantsandConsumptionParticipants—Thelargegrossdomesticproduct(GDP)growthandsubstantialpopulationincreasesoftheHHPopulationgrowth,becauseofitsmagnitude,isoftenscenarioresultinthegreatestprojectednumbersofthedeterminingfactorinlong-termtrendsinthenumberrecreationparticipantsforalmostallactivities(table11-ofrecreationparticipantsandthecollectivetotaldays12).Threeexceptionstothispatternaremotorizedsnowofrecreation.Thenumberofparticipantsengaginginuse,cross-countryskiingandsnowshoeing,andhunting.arecreationactivityinthefuturereflectsbothchangesFormotorizedsnowuse,thereisoverlapbetweentheHHinpercapitaparticipationovertimeandthesizeoftheandHMscenariosintheprojectednumbersofparticipantsfuturepopulation.Similarly,thetotaldaysofrecreationnationallyandintheNorthRegionfor2040and2070.This(consumption)inthefutureisacombinationofthenumberoverlapreflectsthesubstantialprojecteddeclineinperofpeopleparticipatingintheactivityandthemeandayscapitaparticipationinmotorizedsnowuse—toanextentannuallythatparticipantsengageintheactivity.AlthoughthatevenhighpopulationgrowthundertheHHscenariotheremaybemeaningfulchanges(increasesordecreases)cannotoffset—forsomefutureclimates,particularlythehotinpercapitaparticipationandaveragenumberofdaysclimateprojection.Additionally,theabsenceofmotorizedofengagementforindividualactivities(thepercapitasnowuseengagementintheSouthRegiontranslatestoaconsumptionmeasure),populationgrowthtypicallymagnifiesreducednationaltotal,especiallysincelargepopulation(forincreases)oroffsets(fordecreases)thosechanges.increasesareprojectedforthatregionin2040and2070.Table11-12.Projectednumbersofoutdoorrecreationparticipants(millions)forconterminousUnitedStatesandRPAregionsin2040and2070,averagedacrossfiveclimateprojectionswithineachRPAscenario.BaselineLMHLHMHHActivityGeography201220402070204020702040207020402070Developedsiteuse(visitingnaturalprehistoric,and/orhistoricsites;familygatherings;picnicking)ConterminousUnitedStates93.0122.4141.6104.698.6119.4134.9137.4186.844.046.750.664.5North38.045.149.038.634.243.851.550.471.612.414.914.320.8South31.844.854.238.337.519.221.722.129.9RockyMountain8.712.715.710.910.9PacificCoast14.519.722.816.916.0DevelopedcampingConterminousUnitedStates25.330.733.826.824.630.232.634.343.6North9.110.010.38.87.69.910.111.213.3South7.39.210.38.17.69.110.010.313.2RockyMountain3.54.85.74.14.04.75.45.37.4PacificCoast5.36.77.55.85.46.67.17.59.6Natureviewing(viewingorphotographingbirds,otherwildlife,naturalscenery,gathering,other)ConterminousUnitedStates19.125.229.121.520.224.527.628.338.4North7.89.310.07.97.09.19.610.413.3South6.59.211.27.97.79.010.610.414.8RockyMountain1.82.63.22.22.22.63.13.04.3PacificCoast3.04.04.63.43.23.94.44.56.0Birding(viewingorphotographing)ConterminousUnitedStates12.015.917.613.612.215.516.617.822.8North5.16.26.45.34.56.16.17.08.4South4.05.86.74.94.55.66.26.48.6RockyMountain1.01.61.81.31.31.51.71.72.4PacificCoast1.82.42.72.11.92.42.52.73.4DayhikingConterminousUnitedStates31.040.346.934.231.439.243.545.361.7North12.314.215.012.210.514.014.416.120.1South8.411.814.69.89.111.312.913.218.7RockyMountain3.95.87.65.05.15.77.16.710.3PacificCoast6.38.49.77.26.78.29.09.412.5Primitive-areause(visitingwilderness,primitivecamping,backpacking)ConterminousUnitedStates6.88.69.87.36.78.49.29.612.7North2.73.03.22.62.22.93.03.34.1South2.12.83.42.42.22.73.13.24.3RockyMountain0.81.21.51.01.01.21.41.31.9PacificCoast1.21.61.81.41.31.61.71.82.4Continued...11-30FutureofAmerica’sForestsandRangelandsTable11-12continued.Projectednumbersofoutdoorrecreationparticipants(millions)forconterminousUnitedStatesandRPAregionsin2040and2070,averagedacrossfiveclimateprojectionswithineachRPAscenario....ContinuedBaselineLMHLHMHHActivityGeography201220402070204020702040207020402070MountainbikingConterminousUnitedStates6.27.99.96.76.67.79.39.013.6North2.83.34.02.82.73.33.83.85.5South1.72.22.81.81.82.12.52.53.7RockyMountain0.71.11.50.91.01.01.41.22.2PacificCoast1.01.31.61.11.11.31.51.52.1Equestrian(horsebackridingontrails)ConterminousUnitedStates3.44.76.23.94.14.65.95.49.0North1.21.62.01.41.51.62.11.93.2South1.21.72.31.41.41.62.11.93.4RockyMountain0.40.60.90.50.50.60.70.71.2PacificCoast0.60.81.00.60.60.70.90.91.3Motorizedwater(motorboating,waterskiing,personalwatercraftuse)ConterminousUnitedStates27.537.447.731.232.336.245.542.168.8North11.414.116.812.011.813.816.416.024.2South9.513.818.611.412.413.217.515.426.9RockyMountain2.74.15.63.43.64.05.34.78.3PacificCoast3.95.46.74.54.55.26.36.09.4Off-roaddrivingConterminousUnitedStates21.325.328.821.920.824.727.628.037.6North8.08.99.67.77.18.79.69.913.3South7.28.69.77.57.08.49.19.412.0RockyMountain2.73.85.03.33.43.84.74.46.8PacificCoast3.44.04.53.53.23.94.24.45.5Motorizedsnow(snowmobiling)ConterminousUnitedStates4.14.24.33.32.43.83.24.44.7North2.92.62.32.11.22.41.62.82.4RockyMountain0.71.01.20.70.60.80.80.91.3PacificCoast0.50.60.80.50.60.60.70.71.0Fishing(warmwater,coldwater,saltwater,anadromous)ConterminousUnitedStates31.039.345.133.932.538.543.643.960.4North12.213.914.911.910.413.614.215.620.0South12.016.219.314.214.516.019.218.126.1RockyMountain3.04.25.13.63.64.14.84.76.7PacificCoast3.85.05.84.24.14.85.45.57.7Hunting(alltypesoflegalhunting)ConterminousUnitedStates12.713.613.612.210.513.312.814.515.5North5.04.53.74.02.84.33.34.63.8South5.05.86.25.35.15.76.16.27.3RockyMountain1.72.22.51.81.72.02.22.32.9PacificCoast1.01.21.21.11.01.21.21.41.6Developedskiing(downhillskiing,snowboarding)ConterminousUnitedStates11.014.420.011.712.613.818.516.430.5North6.68.010.76.56.97.710.19.116.5RockyMountain1.62.53.92.02.42.43.62.96.1PacificCoast2.83.95.43.13.33.74.84.48.0Undevelopedskiing(cross-countryskiing,snowshoeing)ConterminousUnitedStates6.27.18.06.05.06.87.07.910.3North4.14.34.43.52.64.03.54.65.1RockyMountain1.01.41.71.21.21.31.61.52.4PacificCoast1.11.51.91.31.31.51.81.82.8Swimming(swimminginstreams,lakes,ponds,orocean;snorkeling;scubadiving)ConterminousUnitedStates48.461.773.651.647.859.767.369.498.5North20.222.925.119.216.122.122.525.732.8South16.122.328.218.618.021.625.725.238.2RockyMountain3.85.36.74.54.55.16.26.09.0PacificCoast8.311.213.69.49.310.912.912.618.5Floating(canoeing,kayaking,rafting)ConterminousUnitedStates10.012.114.710.210.011.613.613.420.0North4.44.65.03.93.24.44.45.26.5South3.24.25.53.64.04.05.24.67.7RockyMountain1.01.41.91.21.31.31.81.52.7PacificCoast1.51.92.31.61.51.82.12.13.1ActivitiesareindividualoractivitycompositesderivedfromtheNSRE.Initialparticipantsaredeterminedfromthescenarioadult(16yearsorolder)populationestimatesfortheconterminousUnitedStatesduring2012andinitialestimatesbyactivitybasedonOutdoorFoundationestimatesand/orNSREresponsesfrom2006to2012.NSRE=NationalSurveyonRecreationandtheEnvironment;LM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.2020ResourcesPlanningActAssessment11-31Forhunting,theprojectednumberofparticipantsintheparticipantsin2040.SwimmingisprojectedtobethenextRPANorthRegionundertheHHscenariooverlapswithmost-popularactivity—withabouthalftheparticipantsofprojectionsfortheHMscenarioin2040and2070,reflectingdevelopedsiteuse—followedbydayhiking,fishing,andthelargedeclineinpercapitaparticipationinhuntingundermotorizedwateruse.DevelopedsitecampingroundsoutthetheHHscenarioandtherelativelylowpopulationincreasegreatest-participantactivityaggregateswithprojectionsofprojectedintheNorthRegion,evenundertheHHscenario.between27and34millionparticipantsby2040.EachoftheThecross-countryskiingandsnowshoeingaggregatemost-popularactivitieshasprojectedpercentageincreasesexhibitsasimilarresponse,withoverlapbetweentheHHinparticipantsthatarearound30percentby2040and45andHMscenariointheNorthRegionin2070.percentormoreby2070,relativeto2012.Downhillskiingandsnowboarding,floating,mountainbiking,andequestrianComparingprojectionsundertheLMandHMscenarios,ridingontrails—activitiesthatcurrentlyhavemoderatewiththeirrelativelyequivalentpopulationandGDPtrends,numbersofparticipants—exhibitsomeofthelargestloweratmosphericwarming(LM)tendstofavorincreasedpercentageincreasesinparticipantsbetween2012andnumbersofparticipantsandrecreationconsumption.For2070.Despitethelargepercentageincreases,thenumbersmostactivities,theprojectednumberofparticipantsin2040ofparticipantsinfloating,mountainbiking,andequestrianand2070isslightlygreaterundertheLMscenariocomparedridingontrailsremainmodestin2040and2070relativetototheHMscenario.ThesegeneraldifferencesbetweenthoseseeninmoregeneralandbroadlyaccessibleactivitiestheLMandHMscenariosaremorepronouncedinsomesuchasdayhikingandviewingnature.regions.MeaningfulregionaldifferencestendtooccurfortheRPANorthRegion(formanyactivities)and,beyondtheDaysofEngagement—Ingeneral,ourprojectionsshowNorthRegion,foractivitieswherefutureclimaticchangecontinuedmodestdeclinesintheaveragenumberofdaysmorestronglyinfluencedpercapitaparticipation(e.g.,eachyearthatparticipantsengageinarecreationactivity.motorizedsnowuse,dayhiking,andfloating).TheLMThispatternisconsistentwithrecenttrendsoverthelastscenariohasslightlyhigherGDPandpopulationprojectionsdecadeormore.Ultimately,thoseengaginginoutdoorby2070thantheHMscenario.Thoseslightlyhighertrendsrecreationaredoingsowithlessfrequency,andthattrendalsopromoteslightlygreaterparticipantprojectionsforisprojectedtocontinue.Projecteddeclinesintheaveragemanyactivities.numberofdaysofengagementarecommonacrossactivities,regions,scenarios,andclimateprojections.ThreeactivitiesProjectedlossesinthenumbersofparticipantsengaginginareexceptionstothisgeneralpattern—motorizedwateruse,activitiesin2040and2070relativeto2012wereprimarilymountainbiking,andhunting—althougheachactivitystillconfinedtotheHLscenario,nationallyandregionally.hasprojectedengagementdeclinesinatleastoneregion/Relativelysmallprojectedpopulationgrowthandeconomicscenariocombination.Forhunting,thelackofauniformdevelopmentgainsintheHLscenarioareinsufficienttodeclineacrossregionsandscenariosinprojectedaverageovercomethedeclinesinpercapitaparticipationprojecteddaysofengagementisnoteworthygiventheprojectedformanyactivities.Potentialdeclinesinthenumbersofmarkeddeclinesinpercapitaparticipationinhunting.participantsin2040and2070extendintotheHMscenarioforseveralregionsandnationallyforhunting,motorizedDespitegeneraldeclinesinthemeandaysofrecreationsnowuse,cross-countryskiingandsnowshoeing,andperparticipant,thetotaldaysofrecreationineachactivityfloating.Projecteddeclinesinparticipationforhuntingistypicallyprojectedtoincrease(table11-13).ThisextendintotheHHscenariointheRPANorthRegion.patternresultsbecausethetotalnumberofparticipantsThehuntingresultsreflectthesteepprojecteddeclineinineachactivityistypicallyprojectedtoincreaseinthepercapitahuntingparticipationinthefaceofbothhighfuture.Whenpresent,projecteddeclinesinthetotaldaysatmosphericwarmingandstrongpopulationandeconomicofrecreationforindividualactivitiesaremostcommongrowth.AlthoughmostactivitieshaveprojecteddeclinesundertheHLscenario.Insomecases,thoseprojectedinatleastonescenario-climatefuture,downhillskiinganddeclinesaresubstantial,astheyreflectbothprojectedsnowboarding,equestrianridingontrails,andmotorizeddeclinesinparticipantnumbersandengagementfrequency.wateruseactivitieshaveincreasingnumbersofprojectedForexample,national-leveldaysofrecreationin2070participantsacrossallregions,scenarios,andclimateareprojectedtodeclineby40percentforcross-countryprojections.skiingandsnowshoeing,50percentforsnowmobileuse,and9percentforprimitiveareaactivitiesundertheHLThepresentlymost-popularactivitiesremainthemost-scenario.Whenprojecteddeclinesoccur,theyareoftenpopularinprojectionsoffuturerecreationfor2040andespeciallypronouncedintheRPANorthRegion,withits2070.Developedsiteuse(i.e.,visitingnatural,historic,orlowprojectedpopulationgrowthinthefuture.Aswithprehistoricsites,picnicking,outdoorfamilygatherings)isprojectedparticipation,projecteddeclinesintotaldaysofprojectedtohavethegreatestnumberofparticipantsoftherecreationextendthroughtheHHscenarioinsomeregionsactivityaggregatesbyfar,withbetween104and137million11-32FutureofAmerica’sForestsandRangelandsforsnowmobileuse,cross-countryskiingandsnowshoeing,Projectedpatternsofincrease(ordecrease)inengagementandhunting.Declinesinsnowmobileuseandcross-countrygenerallycontinueinlinearfashionovertheprojectionskiingandsnowshoeingintheNorthRegionresultfromperiod.Discrepanciesbetween2040and2070projectionsthecompoundedinfluenceofatmosphericwarmingandaremostcommonundertheHLscenario.Forexample,decliningpopulation.Percapitaconsumptioninhuntingfortheprojectednumberofbirdingdaysin2040underthetheNorthRegionisprojectedtobemostlystableexceptforHLscenariois7percenthigherthan2012observations,underthehotclimateprojection.Factoringinsubstantiallybutthe2070projectionisareductionof13percentfromdecliningpercapitaparticipationalongsidepopulation2012levels.Similarly,projectionsofdayhikingundertheoutlooks,thenumberofdaysofhuntingintheNorthRegionHLscenarioshowaslightgainintotaldaysfor2040(6isprojectedtodeclinesubstantiallyby2070.percent),whichturnsintoaslightlossof5percentfromTable11-13.Projectednumbersofdays(millions)ofrecreationengagementforconterminousUnitedStatesandRPAregionsin2040and2070,averagedacrossfiveclimateprojectionswithineachRPAscenario.BaselineLMHLHMHHActivityGeography201220402070204020702040207020402070Developedsiteuse(visitingnaturalprehistoric,and/orhistoricsites;familygatherings;picnicking)ConterminousUnitedStates1,1191,4741,7461,2471,1971,4221,6301,6352,284506524586750North446522572441378501626569846166196191273South366520655445472249284289415RockyMountain120173211145143PacificCoast187259308216204DevelopedcampingConterminousUnitedStates198237257206189232249262330North657272635571738097South586876595466727594RockyMountain314250373842494766PacificCoast445559474253556073Natureviewing(viewingorphotographingbirds,otherwildlife,naturalscenery,gathering,other)ConterminousUnitedStates296372407319282361375410504North12514014012096136128155173South103142170122116138157157210RockyMountain263641312835383950PacificCoast435457474152535970Birding(viewingorphotographing)ConterminousUnitedStates172217221185149209198237263North748275715180689191South6386977363838594113RockyMountain121818151317171920PacificCoast223031262129283338DayhikingConterminousUnitedStates473581650500451563597638806North182194188169133190176216230South130165199141132158173179236RockyMountain5376966769769488134PacificCoast110146167122117138154156206Primitive-areause(visitingwilderness,primitivecamping,backpacking)ConterminousUnitedStates111315111013131419North444334445South345434556RockyMountain122222223PacificCoast233223334MountainbikingConterminousUnitedStates125161206136138157193182281North546273534861677097South294054333438494572RockyMountain223346283132433764PacificCoast202633232426343048Equestrian(horsebackridingontrails)ConterminousUnitedStates4661835049586967110North111828161718242136South172436181922292753RockyMountain14141312914121515PacificCoast455434456Continued...2020ResourcesPlanningActAssessment11-33Table11-13continued.Projectednumbersofdays(millions)ofrecreationengagementforconterminousUnitedStatesandRPAregionsin2040and2070,averagedacrossfiveclimateprojectionswithineachRPAscenario.BaselineLMHLHMHHActivityGeography201220402070204020702040207020402070...ContinuedBaselineLMHLHMHHActivityGeography201220402070204020702040207020402070Motorizedwater(motorboating,waterskiing,personalwatercraftuse)ConterminousUnitedStates3665187154294705036785921,109North126162197139145160200185304South169254380208241246355292606RockyMountain284156343740534783PacificCoast4361824848576968116Off-roaddrivingConterminousUnitedStates350414467360355402457450600North10912112810296116129132177South152181209163171180211196258RockyMountain4563795252607169104PacificCoast444951423647465261Motorizedsnow(snowmobiling)ConterminousUnitedStates282624201223162624North23181514716101914RockyMountain345324445PacificCoast334323334Fishing(warmwater,coldwater,saltwater,anadromous)ConterminousUnitedStates501614694537518603676679902North188204209175143199193227269South217288345258279287355319458RockyMountain374957413947525372PacificCoast5874836357717580103Hunting(alltypesoflegalhunting)ConterminousUnitedStates238257259235217255260275308North908065714977588367South106129145120130130154140184RockyMountain232627221824232730PacificCoast192222222124242527Developedskiing(downhillskiing,snowboarding)ConterminousUnitedStates7092132727387113106208North374050322638404670RockyMountain101731131616262052PacificCoast233451273133474085Undevelopedskiing(cross-countryskiing,snowshoeing)ConterminousUnitedStates333637292033293944North22201816818122117RockyMountain5796578811PacificCoast6810778101015Swimming(swimminginstreams,lakes,ponds,orocean;snorkeling;scubadiving)ConterminousUnitedStates5827098605855296787477911,125North211231257189151219215257328South221284368233217271312319482RockyMountain375061424148575683PacificCoast113145174121120139163160231Floating(canoeing,kayaking,rafting)ConterminousUnitedStates6071866058687878115North262830231927273139South212635222525322847RockyMountain5685567711PacificCoast911139911121218ActivitiesareindividualoractivitycompositesderivedfromtheNSRE.Initialparticipantsaredeterminedfromthescenarioadult(16yearsandolder)populationestimatesfortheconterminousUnitedStatesduring2012andinitialestimatesbyactivitybasedonOutdoorFoundationestimatesand/orNSREresponsesfrom2006to2012.NSRE=NationalSurveyonRecreationandtheEnvironment;LM=lowerwarming-moderateU.S.growth;HL=highwarming-lowU.S.growth;HM=highwarming-moderateU.S.growth;HH=highwarming-highU.S.growth.baselineby2070.ThesepatternsarelikewiseprojectedforManagementImplicationsparticipanttotalsfrom2040to2070forbothactivities,albeittoalesspronouncedextent.Furthermore,forbothactivities,OurprojectionsofannualdaysofrecreationactivitiesshowprojectionsunderHLdivergefromtheotherscenarios,increasesacrossmostactivitiesandundermostscenarios.indicatingrelativelymoremeaningfulchangesinnumberofProjectednumbersofrecreationdaysaregreatestforgeneralannualdaysofengagement.activities,suchasdayhiking,viewingnature,developedsiteuse,anddevelopedsitecamping.Ourprojectionsofdays11-34FutureofAmerica’sForestsandRangelandsofengagementarelikelythemostmeaningfulforrecreationavoidpotentialwildfireclosures)orindifferentregions(e.g.,managersbecausethatmetricismostcloselyrelatedtoavoidingplacespronetohurricaneorwinddisturbance).visitation.Recreation-relatednaturalresourcemanagementOverthelongterm,increasedfrequencyorseverityofandpolicydecisionsareoftenmadeinthecontextofpatternsnaturaldisturbancemayinfluencerecreationdemandinwaysincurrentandexpectedfuturerecreationvisitation.Fornotaccountedforinourmodels.example,changesinoccupancyratesatacampground,thenumberofvisitsannuallytoatrail,orthenumberofpermitsConclusionsrequestedbyriverkayakersmightrecommendchangesinmanagementof,andpoliciesfor,recreationresources.AfuturethatincludescontinuingpopulationgrowthandconversionofopenspacetodevelopedlandisprojectedDevelopedsitesandrecreationinfrastructurearelikelytoresultinincreasingpressureontheremainingnaturaltocontinuefacingpressuretomeetrecreationdemand.resourcestoprovidefornature-basedoutdoorrecreation.Developedsiteuse—acompilationofactivitiesincludingAlthoughtherehavebeensomeincreasesinareasofStatevisitinghistoricsitesandpicnicking—anddevelopedsiteparksystemsandlandsmanagedbylandconservancycampingcontinuetobeamongtheleadingactivitiesintermsorganizations,theareaoflandaccessibleforrecreationofparticipantsanddaysofrecreationandarealsoprojectedhasnotkeptpacewithrecentpopulationgrowth.Lookingtoexperiencesomeofthegreatestexpansioninbothmetrics.forward,thepercapitaareaofforestandlandaccessibleforDevelopedfacilitiesprovidingfortheserecreationactivitiesrecreationisprojectedtocontinuetodeclineifpopulationwilllikelycontinuetoseesubstantialandincreasinguseingrowthoccursatthepaceofourhigh-ormoderate-growthfuturedecades.Inadditiontodevelopedsiterecreation,otherscenarios—HH,LM,andHM.ProjectedlossesinpercapitaactivitiesthatfrequentlyrequiredevelopedinfrastructurearerecreationopportunitiesdifferacrossregionsintheUnitedalsoprojectedtoseelargegainsinrecreationconsumptionStates,withdeclinesbeingslowerinregionswithlessinfuturedecades,undermostscenarios.Forexample,populationgrowthandlessconversionoflandstodevelopedmotorizedboatingtypicallyrequiresboatramps,developedlanduses.skiingrequiresskiareainfrastructure,anddayhiking,oneofthemost-popularrecreationactivities,requirestrailsystems.Lookingaheadtothecomingdecades,ourprojectionsoffuturerecreationdemandgenerallyindicateonlymodestOurprojectionsshowlittleindicationofsignificantchangeschanges(bothincreasesanddecreases)intheshareoftheinthetypesofoutdoorrecreationactivitieslikelytobepopulationparticipatinginspecificrecreationactivities.desiredinthecomingdecades,especiallyatthenationalThisisconsistentwithpatternsfoundinrecentdecades.level.Thoseactivitiesthataremost-popularnowareHuntingparticipationisanexceptiontotheotherwiseprojectedtoremainmost-popular.Theactivitieswiththemostlymodestchangesinprojectedparticipation.Moderatehighestprojectedratesofparticipationinfuturedecadestosteepdeclinesinhuntingparticipationareprojectedremainvisitingdevelopedsites,swimming,dayhiking,acrossallscenarios.Themost-popularoutdoorrecreationfishing,andmotorizedwateruse.Thoseactivitiesthatactivitiestoday(viewingnature,dayhiking,andvisitingpresentlyhaverelativelysmallbutenthusiasticparticipantdevelopedrecreationareas)areprojectedtoremainthemost-populationsremainpopularamongarelativelysmallpopularinthecomingdecades.Althoughourprojectionsofcontingentofoutdoorrecreationists.Wedoprojectsteepparticipationyieldamixofincreasesanddecreasesacrossreductionsinpercapitaparticipationforseveralactivitiesactivities,ourprojectionsofengagementfrequencyindicateundermostscenarios:hunting,motorizedsnowuse,anddeclinesacrossalmostallrecreationactivities.Increasesincross-countryskiingandsnowshoeing.engagementfrequencyinthecomingdecadesareprojectedonlyformotorizedwateruse,mountainbiking,andhunting.OurprojectionsofrecreationdemandincludegeneralsupplyOurprojecteddeclinesinengagementareconsistentwithfactors(e.g.,Federalforestlandpercapitawithin200miles)patternsobservedinrecentdecades.butdonotconsiderfactorsrelatedtohowincreasedormore-severenaturaldisturbancemayinfluencerecreationFuturelevelsofatmosphericwarmingandeconomicresourceavailability.Forexample,ourmodelsdonotdevelopmentandpopulationgrowthcanhavediverseconsidertheeffectsoffrequentrecreationresourceclosuresinfluencesonrecreationdemand.Participationandbecauseofwildfireorreduceddesirabilityofrecreationengagementinindividualactivitiesexhibitarangeofresourcesfrompresenceofwildfiresmoke.Researchersresponsivenesstochangesinclimateandeconomicdonotyethaveaveryrichunderstandingofhownaturaldevelopmentandpopulationgrowth.Mostactivitiesdisturbanceinfluencesrecreationbehavior.Intheshortareresponsivetoeithersocioeconomicchangeonlyorterm,ifdisturbancedoesnotalterrecreationdemand,itatmosphericwarmingandsocioeconomicchangejointly.mayinfluencerecreationistdecisionsaboutwhereorwhenTwoactivitiesmostresponsivetoclimatechangearetorecreate.Recreationmanagersmayseerecreationistsmotorizedsnowuseandthecross-countryskiingandoptingtorecreateindifferentseasonsoftheyear(e.g.,to2020ResourcesPlanningActAssessment11-35snowshoeingaggregate,withbothexhibitingsteepprojectedButler,B.;Hewes,J.H.;Dickinson,B.J.;Andrejczyk,K.;Butler,S.M.;declinesinparticipationasatmosphericwarminglevelsMarkowski-Lindsay,M.2016.USDAForestServiceNationalWoodlandincrease.Inaddition,highlevelsofatmosphericwarmingOwnerSurvey:national,regional,andstatestatisticsforfamilyforesthavethelargestnegativeimpactsonrecreationintheRPAandwoodlandownershipswith10+acres,2011–2013.Res.Bull.NorthRegion.DownhillskiingandsnowboardingandNRS-99.NewtownSquare,PA:U.S.DepartmentofAgriculture,ForesthuntingarebothveryresponsivetoincreasesineconomicService,NorthernResearchStation.39p.developmentandpopulationgrowth:theformerexhibitssteepincreasesinprojectedparticipationrateswhiletheCarlson,T.;Barns,C.;Brownlie,D.;Cordell,K.;Dawson,C.;Koch,W.;latterexhibitssteepdeclines.OurprojectionsdonotincludeOye,G.;Ryan,C.2016.AnoverviewofAmerica’sNationalWildernessresidentsofAlaska,Hawaii,ortheU.S.territories.ItisPreservationSystem.JournalofForestry.114(3):289–291.possiblethatfutureclimatechangewillyielddifferentoutcomesforrecreationparticipationandengagementinCenterforCityParkExcellence,TrustforPublicLand[TrustforPublicthoselocales.Land]2018.2018CityParkFacts.SanFrancisco,CA:TrustforPublicLand.16p.Inthepresenceofcontinuedpopulationgrowth,thenumberofindividualsparticipatinginrecreationactivitiesCenterforCityParkExcellence,TrustforPublicLand[TrustforPublicisgenerallyprojectedtoincreaseinthecomingdecades.Land]2020.CityParkFacts2020—AcreageandParkSystemData.However,iffuturepopulationgrowthandeconomicAvailableon-line:https://www.tpl.org/park-data-downloads.(13Julydevelopmentareinsteadmoresimilartoourlow-growth2023).scenario(HL),weprojectsomedeclinesinthenumbersofparticipantsasthemodestpopulationincreasesunderthatGellman,J;Walls,M.;Wibbenmeyer,M.J.2021.Wildfire,smoke,andscenarioareinsufficienttoovercomeprojecteddecliningperoutdoorrecreationinthewesternUnitedStates.WorkingPaper21-22.capitaparticipation.WithinRPAregions,theNorthRegion[placeofpublishingunknown]:ResourcesfortheFuture.32p.https://ismostlikelytohaveprojecteddeclinesinnumbersofmedia.rff.org/documents/WP_21-22.pdf.(31May2022).participantsbecauseofsmallerpopulationincreasesrelativetootherregions.ThegreatestnumbersofparticipantsareHoover,K.2014.Wilderness:overviewandstatistics.CongressionalprojectedundertheHHscenariobecauseitprojectsahigherResearchServiceCRSReportRL31447.17p.populationthantheotherscenarios.Inscenariosofmoderatepopulationgrowthandeconomicdevelopment(theLMandLangner,L.L.;Joyce,L.A.;Wear,D.N.;Prestemon,J.P.;Coulson,D.;HMscenarios),participantnumbersarefrequentlygreaterO’Dea,C.B.2020.Futurescenarios:Atechnicaldocumentsupportingunderlowerlevelsofatmosphericwarming.InaworldwiththeUSDAForestService2020RPAAssessment.Gen.Tech.Rep.highlevelsofatmosphericwarming,however,thegreatestRMRS-GTR-412.FortCollins,CO:U.S.DepartmentofAgriculture,levelsofpopulationgrowthandeconomicexpansion(theForestService,RockyMountainResearchStation.34p.HHscenario)leadtothegreatestnumberofparticipants.Leggett,C.;Horsch,E.;Smith,C.;Unsworth,R.2017.EstimatingLiteratureCitedrecreationvisitationtofederally-managedlands.https://www.doi.gov/sites/doi.gov/files/uploads/final.task1_.report.2017.04.25.pdf.(30Askew,A.;Bowker,J.M.2018.ImpactsofclimatechangeonoutdoorDecember2020).recreationparticipation:outlookto2060.JournalofParkandRecreationAdministration.36:97-120.Love,T.G.Watson,A.E.1992.EffectsoftheGatesParkFireonrecreationchoices.ResearchNoteINT-RN-402,Ogden,UT:U.S.Bowker,J.M.;Askew,A.E.;Cordell,H.K.;Betz,C.J.;Zarnoch,S.J.;DepartmentofAgriculture,ForestService,IntermountainResearchSeymour,L.2012.OutdoorrecreationparticipationintheUnitedStation.7p.States—projectionsto2060:atechnicaldocumentsupportingtheForestService2010RPAAssessment.Gen.Tech.Rep.SRS-160.Asheville,McCaffrey,S.,Toman,E.;Stidham,M.;Shindler,B.2013.SocialNC:U.S.DepartmentofAgricultureForestService,SouthernResearchscienceresearchrelatedtowildfiremanagement:AnoverviewofrecentStation.34p.findingsandfutureresearchneeds.InternationalJournalofWildlandFire.22:15–24.Butler,B.J.;Snyder,S.A.2017.NationalWoodlandOwnerSurvey:familyforestownershipswith1to9acres,2011–2013.Resour.Bull.Mingie,J.C.;Poudyal,N.C.;Bowker,J.M.;Mengak,M.T.;Siry,J.P.NRS-114.NewtownSquare,PA:U.S.DepartmentofAgriculture,Forest2017.Biggamehunterpreferencesforhuntingclubattributes:achoiceService,NorthernResearchStation.9p.experiment.ForestPolicyandEconomics.78:98–106.Butler,B.J.;Butler,S.M.;Caputo,J.;Dias,J.;Robillard,A.;Sass,E.M.NationalAssociationofStateForesters.2019.StateForestersbythe2020.familyforestownershipsoftheUnitedStates,2018:resultsfromNumbers.WashingtonDC:NationalAssociationofStateForesters.30p.theUSDAForestService,NationalWoodlandOwnerSurvey.Gen.Tech.Rep.NRS-199.Madison,WI:U.S.DepartmentofAgriculture,ForestOutdoorFoundation.2018.Outdoorrecreationparticipationreport,Service,NorthernResearchStation.56p.https://doi.org/10.2737/NRS-2018.http://oia.outdoorindustry.org/2018-Participation-Report.(29GTR-199.December2020).OutdoorFoundation.2019.2019Outdoorparticipationreport.http://oia.outdoorindustry.org/2019-Participation-Report.(29December2020).Sass,E.M.;Markowski-Lindsay,M.;Butler,B.J.;Caputo,J.;Hartsell,A.;Huff,E.;Robillard,A.2022.DynamicsoflargecorporateforestlandownershipsintheUnitedStates.JournalofForestry119(4):363–375.Schroeder,S.L.;Schneider,I.E.2010.Wildlandfireandthewildernessvisitorexperience.InternationalJournalofWilderness.16(1):20-25.11-36FutureofAmerica’sForestsandRangelandsShartaj,M.;Suter,J.F.;Warziniack,T.2022.Summercrowds:anUSDAForestService.2012.FutureofAmerica’sforestandrangelands:analysisofUSFScampgroundreservationsduringtheCOVID-19ForestService2010ResourcesPlanningActAssessment.Gen.Tech.pandemic.PloSONE.17(1):e0261833.https://doi.org/10.1371/journal.Rep.WO-87.Washington,DC:U.S.DepartmentofAgriculture,Forestpone.0261833.Service.198p.Smith,J.W.;Leung,Y-F.2018.2018outlookandanalysisletter:TheUSDAForestService.2020.NationalvisitorusemonitoringsurveyvitalstatisticsofAmerica’sstateparksystems.Logan,UT:Instituteresultsnationalsummaryreport.https://www.fs.usda.gov/sites/default/ofOutdoorRecreationandTourism,DepartmentofEnvironmentfiles/2019-National-Visitor-Use-Monitoring-Summary-Report.pdf.andSociety,UtahStateU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vementActPRISMParameter-elevationRegressionsonIndependentSlopesVICVariableInfiltrationCapacityModel(precipitationmodel)RAPRangelandAnalysisPlatformWEAPWaterEvaluationandPlanningRCPRepresentativeConcentrationPathwayREITrealestateinvestmenttrustsWUIwildland-urbaninterfaceRPAResourcesPlanningActRPMSRangelandProductionMonitoringServiceSGCNSpeciesofGreatestConservationNeedSGSsinging-groundsurveySLRsealevelriseSOCsoilorganiccarbonSOSstartofseason(rangelandgrowingseason)SPEIStandardizedPrecipitationEvapotranspirationIndexSSPSharedSocioeconomicPathwaySWAPStateWildlifeActionPlanSWDSsolidwastedisposalsiteTCCTreeCanopyCoverTCSITerrestrialClimateStressIndexTgteragramTIMOtimberlandinvestmentmanagementorganizationsTPOTimberProductOutputUNECEUnitedNationsEconomicCommissionforEuropeA-2FutureofAmerica’sForestsandRangelandsAppendixBListofChapterCitationsChapter1Guo,Jinggang.2023.ForestResources.In:U.S.DepartmentofAgriculture,ForestService.2023.FutureofAmerica’sForestU.S.DepartmentofAgriculture,ForestService.2023.KeyFindingsandRangelands:ForestService2020ResourcesPlanningActofthe2020RPAAssessment.In:U.S.DepartmentofAgriculture,Assessment.Gen.Tech.Rep.WO-102.Washington,DC:6-1–6-38.ForestService.2023.FutureofAmerica’sForestandRangelands:Chapter6.https://doi.org/10.2737/WO-GTR-102-Chap6.ForestService2020ResourcesPlanningActAssessment.Gen.Tech.Rep.WO-102.Washington,DC:1-1–1-11.Chapter1.https://Chapter7doi.org/10.2737/WO-GTR-102-Chap1.Johnston,CraigM.T.;Guo,Jinggang;Prestemon,JeffreyP.2023.Chapter2ForestProducts.In:U.S.DepartmentofAgriculture,ForestService.2023.FutureofAmerica’sForestandRangelands:ForestServiceU.S.DepartmentofAgriculture,ForestService.2023.Introduction.2020ResourcesPlanningActAssessment.Gen.Tech.Rep.WO-In:U.S.DepartmentofAgriculture,ForestService.2023.Futureof102.Washington,DC:7-1–7-26.Chapter7.https://doi.org/10.2737/America’sForestandRangelands:ForestService2020ResourcesWO-GTR-102-Chap7.PlanningActAssessment.Gen.Tech.Rep.WO-102.Washington,DC:2-1–2-7.Chapter2.https://doi.org/10.2737/WO-GTR-102-Chapter8Chap2.Reeves,Matt;Krebs,Michael;McCord,SarahE.;Fitzpatrick,Matt;Chapter3Claassen,Roger;Kachergis,Emily;Krebs,Michael;Metz,LorettaJ.;Hanberry,BriceB.2023.RangelandResources.In:U.S.O’Dea,ClaireB.;Langner,LindaL.;Joyce,LindaA.;Prestemon,DepartmentofAgriculture,ForestService.2023.FutureofAmerica’sJeffreyP.;Wear,DavidN.2023.FutureScenarios.In:U.S.ForestandRangelands:ForestService2020ResourcesPlanningDepartmentofAgriculture,ForestService.2023.FutureofAmerica’sActAssessment.Gen.Tech.Rep.WO-102.Washington,DC:8-1–ForestandRangelands:ForestService2020ResourcesPlanning8-33.Chapter8.https://doi.org/10.2737/WO-GTR-102-Chap8.ActAssessment.Gen.Tech.Rep.WO-102.Washington,DC:3-1–3-13.Chapter3.https://doi.org/10.2737/WO-GTR-102-Chap3.Chapter9Chapter4Warziniack,Travis;Arabi,Mazdak;Froemke,Pamela;Ghosh,Rohini;Heidari,Hadi;Rasmussen,Shaundra;Swartzentruber,Ryan.2023.Riitters,Kurt;Coulston,JohnW.;Mihiar,Christopher;Brooks,EvanWaterResources.In:U.S.DepartmentofAgriculture,ForestService.B.;Greenfield,EricJ.;Nelson,MarkD.;Domke,GrantM.;Mockrin,2023.FutureofAmerica’sForestandRangelands:ForestServiceMirandaH.;Lewis,DavidJ.;Nowak,DavidJ.2023.LandResources.2020ResourcesPlanningActAssessment.Gen.Tech.Rep.WO-102.In:U.S.DepartmentofAgriculture,ForestService.2023.FutureofWashington,DC:9-1–9-20.Chapter9.https://doi.org/10.2737/WO-America’sForestandRangelands:ForestService2020ResourcesGTR-102-Chap9.PlanningActAssessment.Gen.Tech.Rep.WO-102.Washington,DC:4-1–4-37.Chapter4.https://doi.org/10.2737/WO-GTR-102-Chapter10Chap4.Flitcroft,RebeccaL.;Bury,GwendolynnW.;Joyce,LindaA.;Kay,Chapter5ShannonL.;Knowles,MichaelS.;Nelson,MarkD.;Warziniack,Travis.2023.Biodiversity:WildlifeandAquaticBiota.In:U.S.Costanza,JenniferK.;Koch,FrankH.;Reeves,Matt;Potter,KevinDepartmentofAgriculture,ForestService.2023.FutureofAmerica’sM.;Schleeweis,Karen;Riitters,Kurt;Anderson,SarahM.;Brooks,ForestandRangelands:ForestService2020ResourcesPlanningEvanB.;Coulston,JohnW.;Joyce,LindaA.;Nepal,Prakash;ActAssessment.Gen.Tech.Rep.WO-102.Washington,DC:10-Poulter,Benjamin;Prestemon,JeffreyP.;Varner,J.Morgan;Walker,1–10-34.Chapter10.https://doi.org/10.2737/WO-GTR-102-Chap10.DavidM.2023.DisturbancestoForestsandRangelands.In:U.S.DepartmentofAgriculture,ForestService.2023.FutureofAmerica’sChapter11ForestandRangelands:ForestService2020ResourcesPlanningActAssessment.Gen.Tech.Rep.WO-102.Washington,DC:5-1–5-White,EricM.;Askew,AshleyE.;Bowker,J.M.2023.Outdoor55.Chapter5.https://doi.org/10.2737/WO-GTR-102-Chap5.RecreationandWilderness.In:U.S.DepartmentofAgriculture,ForestService.2023.FutureofAmerica’sForestandRangelands:Chapter6ForestService2020ResourcesPlanningActAssessment.Gen.Tech.Rep.WO-102.Washington,DC:11-1–11-37.Chapter11.Coulston,JohnW.;Brooks,EvanB.;Butler,BrettJ.;Costanza,https://doi.org/10.2737/WO-GTR-102-Chap11.JenniferK.;Walker,DavidM.;Domke,GrantM.;Caputo,Jesse;Markowski-Lindsay,Marla;Sass,EmmaM.;Walters,BrianF.;2020ResourcesPlanningActAssessmentB-1